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ENHANCING A MULTIMEDIA PRESENTATION SYSTEM WITH OBJECT-
BASED KNOWLEDGE REPRESENTATION
Abdelmadjid KETFI Jérôme GENSEL Hervé MARTIN
Laboratoire LSR – IMAG, BP 72, 38402 Saint Martin d’Hères, France.
Tél : (33) 4 76 82 72 80, Fax: (33) 4 76 82 72 87
Email : {Firstname.Lastname}@imag.fr
ABSTRACT
This paper deals with the coupling of AROM, an object-
based knowledge representation with V-STORM, a
multimedia presentation system. We propose an AROM
knowledge base which constitutes a generic model for
multimedia presentations. Notably, by instantiating this
knowledge base, a corresponding SMIL file can be
exhibited and parsed by V-STORM in order to be played.
This coupling shows to be relevant for two reasons: first,
by its UML-like formalism, AROM eases the task of a
multimedia presentation author; second, AROM is put in
charge of checking the spatial and temporal consistencies
of the presentation during its description. This way, a
consistent presentation is sent to V-STORM.
1 Introduction
In the last decade, multimedia and, more particularly,
video systems have benefited from a tremendous research
interest. The main reason for this is the increasing ability
computers now have for supporting video data, notably
thanks to unceasing improvements in data compression
formats (as MPEG-4 and MPEG-7), in networks transfer
rates and operating systems [1], and in disk storage
capacity. Unsurprisingly, new applications have risen such
as video on demand, video conferencing and home video
editing which directly benefit from this evolution.
Following this trend, research efforts ([2], [3]) have been
made to extend DataBase Management Systems (DBMS)
so that they support video data types not simply through
Binary Large Objects (BLOB). Indeed, DBMS seem to be
well-suited systems for tackling problems posed by the
video, namely storage, modeling, querying and
presentation. Video data types must be physically
managed apart from other conventional data types in order
to fulfill their performance requirements. Video modeling
must take into account the hierarchical structure of a video
(shots, scenes and sequences) and allow overlapping and
disjoint segment clustering [4]. The video query language
must allow one to query video content using textual
annotations or computed signatures (color, shape, texture,
….) and deal with the dynamic (movements) of objects in
the scenes as well as with semi-structural aspects of
videos and, finally, must offer the possibility of creating
new videos.
We have designed and implemented V-STORM [5] a
video system which captures video data in an object
DBMS. The V-STORM model considers video data from
different perspectives (represented by class hierarchies):
physical (as a BLOB), structural (a video is made up of
shots which are themselves composed of scenes which can
be split into sequences), composition (for editing new
videos using data already stored in the database),
semantics (through an annotation, a video segment is
linked to a database object or a keyword). V-STORM uses
and extends the O2 object DBMS and comes as a tool for
formulating queries on videos, composing a video using
the results of queries, and generating video abstracts. V-
STORM can play videos (or segments of) of its database
but also virtual videos (or segments of) composed through
an O2 interface. Moreover, it is possible to use V-STORM
as a multimedia player for presentations described using
the SMIL [6] standard . This way, V-STORM can be
classified in the family of multimedia presentation
software like GriNS [7] or RealNetworks G2 [8].
We show here how AROM [9], an object-based
knowledge representation system, can be used to help a V-
STORM user to build, in a more declarative way, a
multimedia presentation by instantiating a knowledge base
rather than by writing a SMIL file. Then, we show how
both spatial and temporal consistencies of multimedia
presentation can be maintained by AROM.
The paper is organized as follows : sections 2 and 3
present respectively the V-STORM and AROM systems ;
section 4 describes the AVS model, an AROM knowledge
base which corresponds to a general multimedia
presentation structure ; section 5 gives the related works
before we conclude in section 6.
2 The V-STORM System
V-STORM differentiates between the raw video
stored in the database and the video which is watched and
manipulated by end-users. From a user point of view, a
video is a continuous media which can be played, stopped,
paused, etc. From a DBMS point of view, a video is a
complex object composed of an ordered sequence of
frames, each having a fixed display time. This way, new
virtual videos can be created using frames from different
segments of videos. In V-STORM, the Object Query
Language (OQL) [10] is used (see Figure 1) to extract
video segments to compose virtual videos. Video query
expressions are stored in the databases and the final video
is generated at presentation time.
O2
OQL
Video
DataBase
Video
Composer
Video
Player
Figure 1. The V-STORM architecture
This approach avoids data replication. A video query
returns either a video interval which is a continuous
sequence of frames belonging to the same video, or a
whole video, or an excerpt of a raw video (by combination
of the two previous cases), or a logical extract of a video
stemming from various raw videos. Video composition in
V-STORM is achieved using a set of algebraic operators.
This way a virtual video can be the result of the
concatenation, or the concatenation without duplication
(union), or the intersection, or the difference of two
videos, or, as well, the reduction (by elimination of
duplicate segments) or the finite repetition of a single
video. Annotations in V-STORM are used to describe
salient objects or events appearing in the video. They can
be declared at each level of the video hierarchy.
Annotations are manually created by the users through an
annotation tool. V-STORM also integrates an algorithm to
automatically generate video abstracts. Video abstracts
aims at optimizing the time for watching a video in search
of a particular segment. The user has to provide some
information concerning the expected abstract: its source
(one or more videos), its duration, its structure (which
reflects the structure of the video), and its granularity (in
the video segments might be more relevant than others).
Finally, in order to open V-STORM to the multimedia
presentation standardization, we have developed a SMIL
parser (see Figure 2) so that V-STORM can read a SMIL
document and play the corresponding presentation. Also,
interactivity is possible since V-STORM handles the
presence of anchors for hypermedia links during
presentations. The parser checks the validity of the SMIL
document against the SMIL DTD (extended to support
new temporal operations carried out by V-STORM), then
the different SMIL elements are translated in V-STORM
commands and the video is displayed. Currently, this
parser is limited and does not exploit all the V-STORM
functionalities concerning operations on videos. The work
presented here extends the description of a la SMIL
multimedia presentations in order to better exploit V-
STORM capabilities.
SMIL
Parser
SMIL FileVideo
Player
Figure 2. Using V-STORM with SMIL
3 The AROM System
Object-Based Knowledge Representation Systems
(OBKRS) are known to be declarative systems for
describing, organizing and processing large amounts of
knowledge. In these systems [11], once built, a knowledge
base (KB) can be exploited through various and powerful
inference mechanisms such as classification, method calls,
default values, filters, etc. AROM (which stands for
Associating Relations and Objects for Modeling) is a new
OBKRS which departs from others in two ways. First, in
addition to classes (and objects) which often constitute the
unique and central representation entity in OBKRS,
AROM uses associations (and tuples), similar to those
found in UML [12], to describe and organize links
between objects having common structure and semantics.
Second, in addition to the classical OBKRS inference
mechanisms, AROM integrates an algebraic modeling
language (AML) for expressing operational knowledge in
a declarative way. The AML is used to write constraints,
queries, numerical and symbolic equations involving the
various elements of a KB.
A class in AROM describes a set of objects sharing
common properties and constraints. Each class is
characterized by a set of properties called variables and by
a set of constraints. A variable denotes a property whose
basic type is not a class of the KB. Each variable is
characterized by a set of facets (domain restriction facets,
inference facets, and documentation facets). Expressed in
the AML, constraints are necessary conditions for an
object to belong to the class. Constraints bind together
variables of – or reachable from – the class. The
generalization/specialization relation is a partial order
organizes classes in a hierarchy supported by a simple
inheritance mechanism. An AROM object represents a
distinguishable entity of the modeled domain. Each object
is attached to exactly one class at any moment.
In AROM, like in UML, an association represents a
set of similar links between n (n ≥ 2) classes, being
distinct or not. A link contains objects of the classes (one
for each class) connected by the association. An
association is described by means of roles, variables and
constraints. A role corresponds to the connection between
an association and one of the classes it connects. Each role
has a multiplicity, whose meaning is the same as in UML.
A variable of an association denotes a property associated
with a link and has the same set of available facets as a
class variable. A tuple of an n-ary association having m
variables vi (1 ≤ i ≤ m) is the (n+m)-uple made up of the n
objects of the link and of the m values of the variables of
the association. A tuple is an "instance" of an association.
Constraints involving variables or roles belonging to or
reachable from an association can be written in the AML,
and must be satisfied by every tuple of the association.
Associations are organized in specialization hierarchies.
See Figures 3 and 4 for a textual and a graphical sketches
of a AROM KB dedicated to multimedia presentations.
First introduced in Operations Research, algebraic
modeling languages (AMLs) make it possible to write
systems of equations and/or of constraints, in a formalism
close to mathematical notations. They support the use of
indexed variables and expressions, quantifiers and iterated
operators like ∑ (sum) and ∏ (product), in order to build
expressions such as jJji xxIi ∈∑=∈∀ , . AMLs have
been used for linear and non-linear, for discrete-time
simulation, and recently for constraint programming [13].
In AROM, the AML is used for writing both equations,
constraints, and queries. AML expressions are built from
the following elements: constants, indices and indexed
expressions, operators and functions, iterated operators,
quantified expressions, variables belonging to classes and
associations, and expressions that allow to access to the
tuples of an association. An AML interpreter solves
systems of (non-simultaneous) equations and processes
queries.
Written in Java 1.2, AROM is available1
as a
platform for knowledge representation and exploitation. It
comprises an interactive modeling environment, which
allows one to create, consult, and modify an AROM KB; a
Java API, for developing applications based on AROM,
an interpreter for processing queries and solving sets of
(non-simultaneous) equations written in AML, and
WebAROM, a tool for consulting and editing a KB
through a Web browser.
4 Coupling AROM and V-STORM
As mentioned above, multimedia scenarios played by
V-STORM can be described using SMIL. The starting
point of this study is twofold. We aim first at providing a
UML-like model in order to ease the description of a
multimedia presentation and, second, at reinforcing
consistency regarding spatial and especially temporal
constraints between the components of a multimedia
presentation. It is our conviction that, SMIL like XML
[14], are not intuitive knowledge representation
languages, and one needs to be familiar with their syntax
before to read or write and understand the structure of a
document. So, we propose an AVS (AROM/V-STORM)
model (see Figures 3 and 4), which consists of an AROM
knowledge base whose structure incorporates any SMIL
element used in the description of a multimedia
presentation. This way, we provide a V-STORM user with
an operational UML-like model for describing her
multimedia presentation. Moreover, taking advantage of
1
http://www.inrialpes.fr/romans/arom
the AROM’s AML and type checking, the user can be
informed about the spatial and temporal consistencies of
her presentation.
4.1 An AROM Model for Multimedia
Presentations
Since V-STORM can play any presentation described
with SMIL, our AROM model for multimedia
presentation is SMIL compliant. This means that it
incorporates classes and associations corresponding to
every element that can be found in the structure of a SMIL
document. However, the main objective of the AVS
model is to give the user the opportunity to invoke any
kind of operations V-STORM can performed on a video.
Figure 4 gives a snapshot of the part of our model
dedicated to the video description. The model contains
one hierarchy of classes. The root class is called
Presentation. The various features of a multimedia
presentation are modeled using classes and associations.
Concerning the spatial formatting which describes the
way displayable objects are placed into the presentation
window, it is described by objects of the Layout class,
in accordance with the SMIL recommendation. When a
presentation gathers more than one layout V-STORM
chooses the first layout that matches the user preferences.
This way, V-STORM permits some adaptability
concerning the characteristics of the machine on which the
presentation is played. A layout can be associated with a
root-layout and several regions (described respectively by
classes RootLayout, Region and associations
HasRootLayout and HasRegion) where the media
objects appear. Concerning the time model, a V-STORM
presentation is made up of blocks. Each block can contain
other blocks and/or media objects. Basic media objects
supported by V-STORM are continuous media with an
intrinsic duration (video, audio…) or discrete media
without an intrinsic duration (text, image…). The variable
sync in the Block class determines the temporal
behavior (namely parallel or sequential presentation) of
the elements in the blocks, depending on its value seq or
par. Three temporal information can be associated with a
media object or a block: its duration (variable dur), its
begin and end times (variables begin and end). When
no value is specified for this variable, the duration of a
discrete object is null and the duration of a continuous
object is its natural duration. The semantics concerning
the effective begin of objects linked to a parallel or
sequential block is the same as the one defined in the
SMIL recommendation. Also, every date associated with
an object must be defined as a float value. This is not a
limitation since the model allows to associate to a media
object a set of reaction methods (start, end, load…) in
response to events (click, begin, end…) triggered by other
objects. Compared with an authoring language like
GRiNS, this event-reaction mechanism offers more
synchronization possibilities between objects and through
the AVS model, it is more easy and intuitive to express a
temporal scenario. The knowledge base contains a
Switch class in charge of adapting the presentation to
class: RootLayout
variables:
variable: b_color
type: string
variable: title
type: string
variable: height
type: integer
variable: width
type: integer
class: Region
variables:
variable: b_color
type: string
variable: fit
type: string
variable: title
type: string
variable: top
type: integer
variable: height
type: integer
variable: width
type: integer
class: CommonAttributes
variables:
variable: abstract
type: string
variable: author
type: string
variable: begin
type: float
default: 0
variable: end
type: float
definition: end=begin+dur
variable: dur
type: float
default: 0
definition: dur=end-begin
variable: region
type: string
variable: repeat
type: integer
variable: s_bitrate
type: integer
variable: s_caption
type: boolean
variable: s_language
type: list-of string
cardinality:
min:0
max: *
class: Block
super-class: CommonAttributes
variables:
variable: sync
type: string
default: "seq"
variable: endsync
type: string
class: Element
super-class: CommonAttributes
variables:
variable: media
type: string
variable: src
type: string
variable: alt
documentation: "specifies an
alternate text, if the media can
not be displayed"
type: string
variable: fill
documentation: "if fill=true
so freeze else remove"
type: boolean
association: CBE
roles:
role: block
type: Block
multiplicity:
min: 0
max: *
role: element
type: Element
multiplicity:
min: 0
max: *
Figure 3. An excerpt of the AROM textual description of the AVS model for multimedia presentation showing 5 classes and an association.
In the CommonAttributes abstract class, a definition is given for the end and dur variables using the AML
Figure 4. A view of the Interactive Modeling Environment through which the AVS model can be instantiated. On the left, a view of
the class and association hierarchies. On the right, the UML- like graphical description of the model. .
the system capabilities and settings. The variables found
in this class (s_bitrate, s_captions,
s_language…) are equivalent to the attributes of the
switch element in SMIL. The player will play the first
element of the switch acceptable for presentation. Finally,
the two kinds of navigational links proposed by SMIL (a
and anchor) and allowing interactivity during a
presentation, are represented in the knowledge base by the
A_Link and Anchor_Link classes. The power of the
event-reaction mechanism implemented in V-STORM
allows an author to define more powerful and intuitive
user interaction possibilities than in SMIL. For instance, a
media objects can start some time after the click on
another object, and it can end just after the load of a new
object.
4.2 Building a Multimedia Presentation
To build a multimedia presentation, a V-STORM
user just has to instantiate the AROM KB. For a local KB,
this can be done either by using the AROM Interactive
Modelling Environment (see Figures 4 and 5), or by
completing the ASCII document describing the KB (like
in Figure 3), or by using the Java API of AROM in a
program. For a distant KB, this can be done through a web
browser using WebAROM. Since this instantiation is
made under the control of AROM (type checking,
multiplicity constraint satisfaction, …), both the spatial
and temporal consistencies of the described presentation
are guaranteed.
Figure 5. The editor for instantiating the AVS model
Once this instantiation is performed, an AROM-
SMIL parser we have written is launched and the resulting
SMIL file is sent to the SMIL parser of V-STORM (see
Figure 6).
AROM-SMIL
Parser
VSTORM
AVS Model
for Mulmedia Presentations
User Interface
SMIL
AROM-VSTORM
Parser
AROM-API AROM-IME MODEL.txta WebAROMI
Figure 6. The architecture of the AROM/V-STORM coupling
4.3 Benefits of the AVS Model
The coupling between V-STORM and AROM
combines the video management richness of the former to
the expressing and modelling power of the latter.
Compared to the classical specification and presentation
of multimedia documents, this coupling offers several
advantages.
UML-like description: The AVS-model is described
in a graphical notation close to UML. Object-oriented
analysis and design methods, have shown the relevance of
using graphical notations to improve communication
between all the actors of a design process (for instance
collaborating authors).
Modularity and reuse: The author can edit parts of
the presentation independently and group them to
compose its documents, just by manipulating AROM
objects. This object approach allows the reuse of existing
blocks to compose new presentations, saving a large
amounts of works in the design phase.
Object identity: In an AROM KB, each object has a
unique identifier. This property has been exploited to
prevent inconsistencies due to the assignment of the same
identifier to two different media objects. For the name
given to regions, for instance, the existence of such names
is checked.
Consistency maintenance: When a presentation
contains some inconsistencies, for instance when it says
that an object B starts at the end of an object A, while an
object C starts at the end of B and C starts at the same
time as A, classical multimedia systems ignore or do just
warn about these inconsistencies at play time. Here,
temporal checking is performed by AROM during the
construction of the presentation and the author is warned
about such inconsistencies. This allows sending to the
presentation system a consistent document. This static
checking allows us to obtain a global trace of the
presentation or a timeline view, which aligns all events on
a single axis of time.
Virtual videos: In addition to raw videos, the author
can include in the presentation virtual videos. They
correspond to video objects having no value for their src
variable. Associations (Extraction, Reduction,
Repetition, BinaryOperation) corresponding
to the V-STORM operations for creating virtual videos
have been introduced in the KB. Once these associations
are instantiated, their tuples link a virtual video to the
video(s) (raw or virtual) it is derived from.
Keywords and video abtracts: It is possible to use the
keywords variable to annotate and to formulate queries
on the content of a video. Moreover, the model includes
an AbstractOf association in order to link an abstract
(an object of the VAbstract class), having possibly a
given duration, to a video. Thus, the video can be replaced
by its abstract during the presentation. A VAbstract
object can be created manually or automatically using the
AROM API and the V-STORM video abstract generator.
5 Related Works
For a complete comparison of V-STORM with other
multimedia projects, one can refer to [15]. Among
numerous research works on authoring and presentation
environments for interactive multimedia documents,
Madeus [16] is a very complete environment with a
graphical authoring interface and a spatial formatting
editor. Madeus is based on a constraint-based approach. It
offers flexibility for frequent scenario modifications
carried out by the author before reaching the desired
scenario, a coupling between the editing and presentation
process, and an incremental editing process which consists
in readjusting the solution each time the author adds or
deletes a constraint. Constraint propagation maintains the
consistency of the new scenario: at each editing step, the
author is sure of having a consistent scenario. Our AVS
model also relies on a similar approach since AROM
integrates a constraint solver. The AML allows
expressions of constraints involving classes, associations,
objects or tuples. But for authoring, we put the emphasis
on a yet more declarative approach through the use a
UML-like model in which constraints are implicitly
embedded into temporal and spatial operators. Also,
unlike V-STORM, other presentation tools pay few
attention to the video data type management. Finally, to
our knowledge, this study is the first attempt to benefit
from the expressing power of a object-based knowledge
representation system to describe and check the
consistency of a multimedia presentation.
6 Conclusion
This paper presents a first attempt to couple an
object-based knowledge representation system (OBKRS)
called AROM, with a multimedia presentation authoring
tool named V-STORM. This coupling has three main
results. First, the multimedia presentation scenario can be
modelled using UML diagram class-like description of
AROM which shown to be more intuitive than a SMIL
file. Second, the inference and consistency engines of
AROM checks the presentation against validity. Third, the
richness of V-STORM video operators is better exploited.
The AROM KB proposed here, called AVS, is a generic
model for multimedia presentations. Classes and
associations of the AVS model just have to be instantiated
to create an effective multimedia presentation. Notably,
this model incorporates every characteristic of SMIL
elements for describing how to arrange media objects in a
scenario. A parser has been written to translate such an
AROM KB into a SMIL document. At its turn, this SMIL
document is parsed by V-STORM and the presentation is
played.
Future works will concern the integration of the V-
STORM video query language into the AROM model.
The idea here is to substitute the OQL query language by
the algebraic modelling language of AROM. Eventually, a
parser will directly connect AROM to V-STORM, without
having recourse to the existing AROM/SMIL parser.
Also, parallel works we make [17] for a better use of
database capabilities in the context of Web presentations
could be integrated within the AVS model.
7 References
[1] A. Laursen, J. Olkin and M. Porter, Oracle Media
Server: providing consumer interactive access to
Multimedia data, SIGMOD, 1994.
[2] K. Nwosu, B. Thuraisingham and B. Berra,
Multimedia Database Systems: design and
implementation strategies (Kluwer Academic
Publishers, 1996).
[3] B. Ozden, R. Rastogori and A. Silberschatz,
Multimedia Database Systems, Issues and Research
Directions (Springer-Verlag, 1996).
[4] R. Weiss, A. Duda and D. Gifford, Composition and
Search with a Video Algebra, IEEE multimedia, ,
Spring Ed., 1995, 12-25.
[5] R. Lozano, M. Adiba, F. Mocellin and H. Martin, An
Object DBMS for Multimedia Presentations
including Video Data, Proc. of ECOOP’98
Workshop Reader, Springer Verlag, Lecture Notes in
Computer Science, 1543, 1998.
[6] W3C Recommendation: Synchronized Multimedia
Integration Language (SMIL) 1.0 Specification
http://www.w3.org/TR/REC-smil
[7] GriNS Authoring Software,
http://www.oratrix.com/GRiNS/index.html
[8] RealNetworks G2, http://www.realnetworks.com
[9] M. Page, J. Gensel, C. Capponi, C. Bruley, P.
Genoud, D. Ziébelin, D. Bardou and V. Dupierris, A
New Approach in Object-Based Knowledge
Representation : the AROM System, IEA/AIE-2001,
June 4-7, Budapest, Hungary, 2001, 113-118.
[10] R.G.G. Cattell and D. Barry, The Object Database
Standard : ODMG 2.0, (Morgan Kaufmann,1997).
[11] R. J. Brachman and J. G. Schmolze, An Overview of
the KL-ONE Knowledge Representation System,
Communications of the ACM, 31 (4), , 1988, 382-401
[12] J. Rumbaugh, I. Jacobson and G. Booch, The
Unified Modeling Language Reference Manual.,
(Addison-Wesley, 1999).
[13] P. Van Hentenryck, The OPL Optimization
Programming Language, (MIT Press, 1999).
[14] W3C Recommendation: Extensible Markup
Language (XML) 1.0 (Second Edition)
http://www.w3.org/TR/REC-xml
[15] R. Lozano, Intégration de données video dans un
SGBD à objets, PhD Thesis (in French), Joseph
Fourier University, Grenoble, France, 2000.
[16] M. Jourdan, N. Layaïda, C. Roisin, L. Sabry-Ismaïl
and L. Tardif, Madeus, an Authoring Environment
for Interactive Multimedia Documents, in ACM
Multimedia, Bristol, UK, 1998, 267-272,.
[17] Mulhem and H. Martin, From Database to Web
multimedia Documents, in Journal of Multimedia
Tools and Applications (to appear), 2001.

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Enhancing a Multimedia Presentation System with Object-Based Knowledge Representation

  • 1. ENHANCING A MULTIMEDIA PRESENTATION SYSTEM WITH OBJECT- BASED KNOWLEDGE REPRESENTATION Abdelmadjid KETFI Jérôme GENSEL Hervé MARTIN Laboratoire LSR – IMAG, BP 72, 38402 Saint Martin d’Hères, France. Tél : (33) 4 76 82 72 80, Fax: (33) 4 76 82 72 87 Email : {Firstname.Lastname}@imag.fr ABSTRACT This paper deals with the coupling of AROM, an object- based knowledge representation with V-STORM, a multimedia presentation system. We propose an AROM knowledge base which constitutes a generic model for multimedia presentations. Notably, by instantiating this knowledge base, a corresponding SMIL file can be exhibited and parsed by V-STORM in order to be played. This coupling shows to be relevant for two reasons: first, by its UML-like formalism, AROM eases the task of a multimedia presentation author; second, AROM is put in charge of checking the spatial and temporal consistencies of the presentation during its description. This way, a consistent presentation is sent to V-STORM. 1 Introduction In the last decade, multimedia and, more particularly, video systems have benefited from a tremendous research interest. The main reason for this is the increasing ability computers now have for supporting video data, notably thanks to unceasing improvements in data compression formats (as MPEG-4 and MPEG-7), in networks transfer rates and operating systems [1], and in disk storage capacity. Unsurprisingly, new applications have risen such as video on demand, video conferencing and home video editing which directly benefit from this evolution. Following this trend, research efforts ([2], [3]) have been made to extend DataBase Management Systems (DBMS) so that they support video data types not simply through Binary Large Objects (BLOB). Indeed, DBMS seem to be well-suited systems for tackling problems posed by the video, namely storage, modeling, querying and presentation. Video data types must be physically managed apart from other conventional data types in order to fulfill their performance requirements. Video modeling must take into account the hierarchical structure of a video (shots, scenes and sequences) and allow overlapping and disjoint segment clustering [4]. The video query language must allow one to query video content using textual annotations or computed signatures (color, shape, texture, ….) and deal with the dynamic (movements) of objects in the scenes as well as with semi-structural aspects of videos and, finally, must offer the possibility of creating new videos. We have designed and implemented V-STORM [5] a video system which captures video data in an object DBMS. The V-STORM model considers video data from different perspectives (represented by class hierarchies): physical (as a BLOB), structural (a video is made up of shots which are themselves composed of scenes which can be split into sequences), composition (for editing new videos using data already stored in the database), semantics (through an annotation, a video segment is linked to a database object or a keyword). V-STORM uses and extends the O2 object DBMS and comes as a tool for formulating queries on videos, composing a video using the results of queries, and generating video abstracts. V- STORM can play videos (or segments of) of its database but also virtual videos (or segments of) composed through an O2 interface. Moreover, it is possible to use V-STORM as a multimedia player for presentations described using the SMIL [6] standard . This way, V-STORM can be classified in the family of multimedia presentation software like GriNS [7] or RealNetworks G2 [8]. We show here how AROM [9], an object-based knowledge representation system, can be used to help a V- STORM user to build, in a more declarative way, a multimedia presentation by instantiating a knowledge base rather than by writing a SMIL file. Then, we show how both spatial and temporal consistencies of multimedia presentation can be maintained by AROM. The paper is organized as follows : sections 2 and 3 present respectively the V-STORM and AROM systems ; section 4 describes the AVS model, an AROM knowledge base which corresponds to a general multimedia presentation structure ; section 5 gives the related works before we conclude in section 6. 2 The V-STORM System V-STORM differentiates between the raw video stored in the database and the video which is watched and manipulated by end-users. From a user point of view, a video is a continuous media which can be played, stopped, paused, etc. From a DBMS point of view, a video is a complex object composed of an ordered sequence of frames, each having a fixed display time. This way, new virtual videos can be created using frames from different segments of videos. In V-STORM, the Object Query
  • 2. Language (OQL) [10] is used (see Figure 1) to extract video segments to compose virtual videos. Video query expressions are stored in the databases and the final video is generated at presentation time. O2 OQL Video DataBase Video Composer Video Player Figure 1. The V-STORM architecture This approach avoids data replication. A video query returns either a video interval which is a continuous sequence of frames belonging to the same video, or a whole video, or an excerpt of a raw video (by combination of the two previous cases), or a logical extract of a video stemming from various raw videos. Video composition in V-STORM is achieved using a set of algebraic operators. This way a virtual video can be the result of the concatenation, or the concatenation without duplication (union), or the intersection, or the difference of two videos, or, as well, the reduction (by elimination of duplicate segments) or the finite repetition of a single video. Annotations in V-STORM are used to describe salient objects or events appearing in the video. They can be declared at each level of the video hierarchy. Annotations are manually created by the users through an annotation tool. V-STORM also integrates an algorithm to automatically generate video abstracts. Video abstracts aims at optimizing the time for watching a video in search of a particular segment. The user has to provide some information concerning the expected abstract: its source (one or more videos), its duration, its structure (which reflects the structure of the video), and its granularity (in the video segments might be more relevant than others). Finally, in order to open V-STORM to the multimedia presentation standardization, we have developed a SMIL parser (see Figure 2) so that V-STORM can read a SMIL document and play the corresponding presentation. Also, interactivity is possible since V-STORM handles the presence of anchors for hypermedia links during presentations. The parser checks the validity of the SMIL document against the SMIL DTD (extended to support new temporal operations carried out by V-STORM), then the different SMIL elements are translated in V-STORM commands and the video is displayed. Currently, this parser is limited and does not exploit all the V-STORM functionalities concerning operations on videos. The work presented here extends the description of a la SMIL multimedia presentations in order to better exploit V- STORM capabilities. SMIL Parser SMIL FileVideo Player Figure 2. Using V-STORM with SMIL 3 The AROM System Object-Based Knowledge Representation Systems (OBKRS) are known to be declarative systems for describing, organizing and processing large amounts of knowledge. In these systems [11], once built, a knowledge base (KB) can be exploited through various and powerful inference mechanisms such as classification, method calls, default values, filters, etc. AROM (which stands for Associating Relations and Objects for Modeling) is a new OBKRS which departs from others in two ways. First, in addition to classes (and objects) which often constitute the unique and central representation entity in OBKRS, AROM uses associations (and tuples), similar to those found in UML [12], to describe and organize links between objects having common structure and semantics. Second, in addition to the classical OBKRS inference mechanisms, AROM integrates an algebraic modeling language (AML) for expressing operational knowledge in a declarative way. The AML is used to write constraints, queries, numerical and symbolic equations involving the various elements of a KB. A class in AROM describes a set of objects sharing common properties and constraints. Each class is characterized by a set of properties called variables and by a set of constraints. A variable denotes a property whose basic type is not a class of the KB. Each variable is characterized by a set of facets (domain restriction facets, inference facets, and documentation facets). Expressed in the AML, constraints are necessary conditions for an object to belong to the class. Constraints bind together variables of – or reachable from – the class. The generalization/specialization relation is a partial order organizes classes in a hierarchy supported by a simple inheritance mechanism. An AROM object represents a distinguishable entity of the modeled domain. Each object is attached to exactly one class at any moment. In AROM, like in UML, an association represents a set of similar links between n (n ≥ 2) classes, being distinct or not. A link contains objects of the classes (one for each class) connected by the association. An association is described by means of roles, variables and constraints. A role corresponds to the connection between an association and one of the classes it connects. Each role has a multiplicity, whose meaning is the same as in UML. A variable of an association denotes a property associated with a link and has the same set of available facets as a class variable. A tuple of an n-ary association having m
  • 3. variables vi (1 ≤ i ≤ m) is the (n+m)-uple made up of the n objects of the link and of the m values of the variables of the association. A tuple is an "instance" of an association. Constraints involving variables or roles belonging to or reachable from an association can be written in the AML, and must be satisfied by every tuple of the association. Associations are organized in specialization hierarchies. See Figures 3 and 4 for a textual and a graphical sketches of a AROM KB dedicated to multimedia presentations. First introduced in Operations Research, algebraic modeling languages (AMLs) make it possible to write systems of equations and/or of constraints, in a formalism close to mathematical notations. They support the use of indexed variables and expressions, quantifiers and iterated operators like ∑ (sum) and ∏ (product), in order to build expressions such as jJji xxIi ∈∑=∈∀ , . AMLs have been used for linear and non-linear, for discrete-time simulation, and recently for constraint programming [13]. In AROM, the AML is used for writing both equations, constraints, and queries. AML expressions are built from the following elements: constants, indices and indexed expressions, operators and functions, iterated operators, quantified expressions, variables belonging to classes and associations, and expressions that allow to access to the tuples of an association. An AML interpreter solves systems of (non-simultaneous) equations and processes queries. Written in Java 1.2, AROM is available1 as a platform for knowledge representation and exploitation. It comprises an interactive modeling environment, which allows one to create, consult, and modify an AROM KB; a Java API, for developing applications based on AROM, an interpreter for processing queries and solving sets of (non-simultaneous) equations written in AML, and WebAROM, a tool for consulting and editing a KB through a Web browser. 4 Coupling AROM and V-STORM As mentioned above, multimedia scenarios played by V-STORM can be described using SMIL. The starting point of this study is twofold. We aim first at providing a UML-like model in order to ease the description of a multimedia presentation and, second, at reinforcing consistency regarding spatial and especially temporal constraints between the components of a multimedia presentation. It is our conviction that, SMIL like XML [14], are not intuitive knowledge representation languages, and one needs to be familiar with their syntax before to read or write and understand the structure of a document. So, we propose an AVS (AROM/V-STORM) model (see Figures 3 and 4), which consists of an AROM knowledge base whose structure incorporates any SMIL element used in the description of a multimedia presentation. This way, we provide a V-STORM user with an operational UML-like model for describing her multimedia presentation. Moreover, taking advantage of 1 http://www.inrialpes.fr/romans/arom the AROM’s AML and type checking, the user can be informed about the spatial and temporal consistencies of her presentation. 4.1 An AROM Model for Multimedia Presentations Since V-STORM can play any presentation described with SMIL, our AROM model for multimedia presentation is SMIL compliant. This means that it incorporates classes and associations corresponding to every element that can be found in the structure of a SMIL document. However, the main objective of the AVS model is to give the user the opportunity to invoke any kind of operations V-STORM can performed on a video. Figure 4 gives a snapshot of the part of our model dedicated to the video description. The model contains one hierarchy of classes. The root class is called Presentation. The various features of a multimedia presentation are modeled using classes and associations. Concerning the spatial formatting which describes the way displayable objects are placed into the presentation window, it is described by objects of the Layout class, in accordance with the SMIL recommendation. When a presentation gathers more than one layout V-STORM chooses the first layout that matches the user preferences. This way, V-STORM permits some adaptability concerning the characteristics of the machine on which the presentation is played. A layout can be associated with a root-layout and several regions (described respectively by classes RootLayout, Region and associations HasRootLayout and HasRegion) where the media objects appear. Concerning the time model, a V-STORM presentation is made up of blocks. Each block can contain other blocks and/or media objects. Basic media objects supported by V-STORM are continuous media with an intrinsic duration (video, audio…) or discrete media without an intrinsic duration (text, image…). The variable sync in the Block class determines the temporal behavior (namely parallel or sequential presentation) of the elements in the blocks, depending on its value seq or par. Three temporal information can be associated with a media object or a block: its duration (variable dur), its begin and end times (variables begin and end). When no value is specified for this variable, the duration of a discrete object is null and the duration of a continuous object is its natural duration. The semantics concerning the effective begin of objects linked to a parallel or sequential block is the same as the one defined in the SMIL recommendation. Also, every date associated with an object must be defined as a float value. This is not a limitation since the model allows to associate to a media object a set of reaction methods (start, end, load…) in response to events (click, begin, end…) triggered by other objects. Compared with an authoring language like GRiNS, this event-reaction mechanism offers more synchronization possibilities between objects and through the AVS model, it is more easy and intuitive to express a temporal scenario. The knowledge base contains a Switch class in charge of adapting the presentation to
  • 4. class: RootLayout variables: variable: b_color type: string variable: title type: string variable: height type: integer variable: width type: integer class: Region variables: variable: b_color type: string variable: fit type: string variable: title type: string variable: top type: integer variable: height type: integer variable: width type: integer class: CommonAttributes variables: variable: abstract type: string variable: author type: string variable: begin type: float default: 0 variable: end type: float definition: end=begin+dur variable: dur type: float default: 0 definition: dur=end-begin variable: region type: string variable: repeat type: integer variable: s_bitrate type: integer variable: s_caption type: boolean variable: s_language type: list-of string cardinality: min:0 max: * class: Block super-class: CommonAttributes variables: variable: sync type: string default: "seq" variable: endsync type: string class: Element super-class: CommonAttributes variables: variable: media type: string variable: src type: string variable: alt documentation: "specifies an alternate text, if the media can not be displayed" type: string variable: fill documentation: "if fill=true so freeze else remove" type: boolean association: CBE roles: role: block type: Block multiplicity: min: 0 max: * role: element type: Element multiplicity: min: 0 max: * Figure 3. An excerpt of the AROM textual description of the AVS model for multimedia presentation showing 5 classes and an association. In the CommonAttributes abstract class, a definition is given for the end and dur variables using the AML Figure 4. A view of the Interactive Modeling Environment through which the AVS model can be instantiated. On the left, a view of the class and association hierarchies. On the right, the UML- like graphical description of the model. . the system capabilities and settings. The variables found in this class (s_bitrate, s_captions, s_language…) are equivalent to the attributes of the switch element in SMIL. The player will play the first element of the switch acceptable for presentation. Finally, the two kinds of navigational links proposed by SMIL (a and anchor) and allowing interactivity during a presentation, are represented in the knowledge base by the A_Link and Anchor_Link classes. The power of the event-reaction mechanism implemented in V-STORM allows an author to define more powerful and intuitive user interaction possibilities than in SMIL. For instance, a media objects can start some time after the click on
  • 5. another object, and it can end just after the load of a new object. 4.2 Building a Multimedia Presentation To build a multimedia presentation, a V-STORM user just has to instantiate the AROM KB. For a local KB, this can be done either by using the AROM Interactive Modelling Environment (see Figures 4 and 5), or by completing the ASCII document describing the KB (like in Figure 3), or by using the Java API of AROM in a program. For a distant KB, this can be done through a web browser using WebAROM. Since this instantiation is made under the control of AROM (type checking, multiplicity constraint satisfaction, …), both the spatial and temporal consistencies of the described presentation are guaranteed. Figure 5. The editor for instantiating the AVS model Once this instantiation is performed, an AROM- SMIL parser we have written is launched and the resulting SMIL file is sent to the SMIL parser of V-STORM (see Figure 6). AROM-SMIL Parser VSTORM AVS Model for Mulmedia Presentations User Interface SMIL AROM-VSTORM Parser AROM-API AROM-IME MODEL.txta WebAROMI Figure 6. The architecture of the AROM/V-STORM coupling 4.3 Benefits of the AVS Model The coupling between V-STORM and AROM combines the video management richness of the former to the expressing and modelling power of the latter. Compared to the classical specification and presentation of multimedia documents, this coupling offers several advantages. UML-like description: The AVS-model is described in a graphical notation close to UML. Object-oriented analysis and design methods, have shown the relevance of using graphical notations to improve communication between all the actors of a design process (for instance collaborating authors). Modularity and reuse: The author can edit parts of the presentation independently and group them to compose its documents, just by manipulating AROM objects. This object approach allows the reuse of existing blocks to compose new presentations, saving a large amounts of works in the design phase. Object identity: In an AROM KB, each object has a unique identifier. This property has been exploited to prevent inconsistencies due to the assignment of the same identifier to two different media objects. For the name given to regions, for instance, the existence of such names is checked. Consistency maintenance: When a presentation contains some inconsistencies, for instance when it says that an object B starts at the end of an object A, while an object C starts at the end of B and C starts at the same time as A, classical multimedia systems ignore or do just warn about these inconsistencies at play time. Here, temporal checking is performed by AROM during the construction of the presentation and the author is warned about such inconsistencies. This allows sending to the presentation system a consistent document. This static checking allows us to obtain a global trace of the presentation or a timeline view, which aligns all events on a single axis of time. Virtual videos: In addition to raw videos, the author can include in the presentation virtual videos. They correspond to video objects having no value for their src variable. Associations (Extraction, Reduction, Repetition, BinaryOperation) corresponding to the V-STORM operations for creating virtual videos have been introduced in the KB. Once these associations are instantiated, their tuples link a virtual video to the video(s) (raw or virtual) it is derived from. Keywords and video abtracts: It is possible to use the keywords variable to annotate and to formulate queries on the content of a video. Moreover, the model includes an AbstractOf association in order to link an abstract (an object of the VAbstract class), having possibly a given duration, to a video. Thus, the video can be replaced by its abstract during the presentation. A VAbstract object can be created manually or automatically using the AROM API and the V-STORM video abstract generator. 5 Related Works For a complete comparison of V-STORM with other multimedia projects, one can refer to [15]. Among numerous research works on authoring and presentation environments for interactive multimedia documents, Madeus [16] is a very complete environment with a graphical authoring interface and a spatial formatting editor. Madeus is based on a constraint-based approach. It offers flexibility for frequent scenario modifications carried out by the author before reaching the desired scenario, a coupling between the editing and presentation process, and an incremental editing process which consists in readjusting the solution each time the author adds or
  • 6. deletes a constraint. Constraint propagation maintains the consistency of the new scenario: at each editing step, the author is sure of having a consistent scenario. Our AVS model also relies on a similar approach since AROM integrates a constraint solver. The AML allows expressions of constraints involving classes, associations, objects or tuples. But for authoring, we put the emphasis on a yet more declarative approach through the use a UML-like model in which constraints are implicitly embedded into temporal and spatial operators. Also, unlike V-STORM, other presentation tools pay few attention to the video data type management. Finally, to our knowledge, this study is the first attempt to benefit from the expressing power of a object-based knowledge representation system to describe and check the consistency of a multimedia presentation. 6 Conclusion This paper presents a first attempt to couple an object-based knowledge representation system (OBKRS) called AROM, with a multimedia presentation authoring tool named V-STORM. This coupling has three main results. First, the multimedia presentation scenario can be modelled using UML diagram class-like description of AROM which shown to be more intuitive than a SMIL file. Second, the inference and consistency engines of AROM checks the presentation against validity. Third, the richness of V-STORM video operators is better exploited. The AROM KB proposed here, called AVS, is a generic model for multimedia presentations. Classes and associations of the AVS model just have to be instantiated to create an effective multimedia presentation. Notably, this model incorporates every characteristic of SMIL elements for describing how to arrange media objects in a scenario. A parser has been written to translate such an AROM KB into a SMIL document. At its turn, this SMIL document is parsed by V-STORM and the presentation is played. Future works will concern the integration of the V- STORM video query language into the AROM model. The idea here is to substitute the OQL query language by the algebraic modelling language of AROM. Eventually, a parser will directly connect AROM to V-STORM, without having recourse to the existing AROM/SMIL parser. Also, parallel works we make [17] for a better use of database capabilities in the context of Web presentations could be integrated within the AVS model. 7 References [1] A. Laursen, J. Olkin and M. Porter, Oracle Media Server: providing consumer interactive access to Multimedia data, SIGMOD, 1994. [2] K. Nwosu, B. Thuraisingham and B. Berra, Multimedia Database Systems: design and implementation strategies (Kluwer Academic Publishers, 1996). [3] B. Ozden, R. Rastogori and A. Silberschatz, Multimedia Database Systems, Issues and Research Directions (Springer-Verlag, 1996). [4] R. Weiss, A. Duda and D. Gifford, Composition and Search with a Video Algebra, IEEE multimedia, , Spring Ed., 1995, 12-25. [5] R. Lozano, M. Adiba, F. Mocellin and H. Martin, An Object DBMS for Multimedia Presentations including Video Data, Proc. of ECOOP’98 Workshop Reader, Springer Verlag, Lecture Notes in Computer Science, 1543, 1998. [6] W3C Recommendation: Synchronized Multimedia Integration Language (SMIL) 1.0 Specification http://www.w3.org/TR/REC-smil [7] GriNS Authoring Software, http://www.oratrix.com/GRiNS/index.html [8] RealNetworks G2, http://www.realnetworks.com [9] M. Page, J. Gensel, C. Capponi, C. Bruley, P. Genoud, D. Ziébelin, D. Bardou and V. Dupierris, A New Approach in Object-Based Knowledge Representation : the AROM System, IEA/AIE-2001, June 4-7, Budapest, Hungary, 2001, 113-118. [10] R.G.G. Cattell and D. Barry, The Object Database Standard : ODMG 2.0, (Morgan Kaufmann,1997). [11] R. J. Brachman and J. G. Schmolze, An Overview of the KL-ONE Knowledge Representation System, Communications of the ACM, 31 (4), , 1988, 382-401 [12] J. Rumbaugh, I. Jacobson and G. Booch, The Unified Modeling Language Reference Manual., (Addison-Wesley, 1999). [13] P. Van Hentenryck, The OPL Optimization Programming Language, (MIT Press, 1999). [14] W3C Recommendation: Extensible Markup Language (XML) 1.0 (Second Edition) http://www.w3.org/TR/REC-xml [15] R. Lozano, Intégration de données video dans un SGBD à objets, PhD Thesis (in French), Joseph Fourier University, Grenoble, France, 2000. [16] M. Jourdan, N. Layaïda, C. Roisin, L. Sabry-Ismaïl and L. Tardif, Madeus, an Authoring Environment for Interactive Multimedia Documents, in ACM Multimedia, Bristol, UK, 1998, 267-272,. [17] Mulhem and H. Martin, From Database to Web multimedia Documents, in Journal of Multimedia Tools and Applications (to appear), 2001.