This document discusses research on detecting deception in real-time audio and video streams. It outlines challenges in synchronizing, capturing, indexing and analyzing multiple streams. It proposes using MPEG-7 semantic annotations to generate knowledge bases for analysis. The research tests infrastructure for capturing, storing and retrieving segmented streams in SQL Server 2008. It also demonstrates prototype avatar animation controlled by Python scripts. Further studies are needed on the visual concept models and detection analysis engine.
One-stop shop for software development informationAftab Iqbal
Talks about the issues which developers face while interacting with the many software repositories and the questions they usually have in their mind while search. Introduce the linked data approach to integrate the information from different software repositories.
A Novel Biometric Technique Benchmark Analysis For Selection Of Best Biometri...CSCJournals
A biometric security is a technique by means of which digital contents are protected by a cryptographic key generated from the biometric features of a person like Retina, Iris, Fingerprint, Face, Voice and so on. Normally the digital contents like documents are protected by a cryptographic key generated from a unique password. The process in irreversible, i.e the key can be generated from the password but not the vice versa. Passwords are relatively easy to hack as most of the users keep their personal information like date of birth as password and also password length has a limit as human beings cannot remember a password of significantly large length. Hence guessing the password of a user, whose significant information is available, is easier. Therefore off late lot of emphasis has been given to biometric features. Biometric features of no two people are same. For example the finger prints or the face of any two people differ. Hence if a template (alphanumeric or binary representation of features from a biometric data) is selected for the key generation than cracking them for accessing information becomes significantly difficult. But as with every advantage comes certain limitations also. The keys are not time invariant. Templates tends to change based on the data acquisition, or with time. For example the finger prints or palm prints changes with ages. Iris, retina and face features changes with change in light intensity during the acquisition phase. Fingerprint features changes with change in the orientation of the finger while scanning. In a classic authentication problem, such variability’s can be easily dealt with by keeping a threshold for the acceptance of the features. Such acceptance threshold is not applicable for the case of biometric templates. Even slightest of the variability in the templates changes the generated key, therefore causing a high false rejection rate. Hence in this work we analyze the most accepted biometric features and techniques for key generation and propose the most invariable technique in terms of data acquisition invariability. The work analyzes Iris, Face, Fingerprint and Palm prints for analysis of the biometric template generation and key generation form the templates. Further a unique benchmark analysis technique is proposed for quantifying the quality of a biometric model or features.
Certified Deep Learning Specialist (CDLS)GICTTraining
GICT Certified Deep Learning Specialist (CDLS) course will focus on the implementation of the newest libraries for implementing Deep Learning
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A survey on encryption algorithms for data securityeSAT Journals
Abstract In current world the security is more important in all fields. The data that is transferred between any must be retrieved securely. For this secure data retrieval we use cryptographic solutions. Disruption Tolerant Network (DTN) technologies have become successful solutions that permit wireless devices to speak with one another and access the guidance dependably by exploiting auxiliary storage nodes. The cryptographic solutions used for the retrieval of data are encryption algorithms. In this paper we discussed several algorithms used for the secure data retrieval in all fields. Keywords: Security, Cryptography, DTN and Encryption
Graphical Based Password for Android Phones using Keystroke Dynamics - A SurveyIJSRD
Technology has elevated to grab an important position in humans life, the best example is smartphones. They offer access to network as well as online banking transactions, where simplification of human labour affects security and user authentication, and passwords are first line of defense, it’s crucial to pick a strong password. Online banking applications currently use alphanumerical usernames and passwords for authentication, which are exposed to eves dropping, attacks, and shoulder surfing. Users often choose either easy to remember passwords, which can be easily guessed or difficult ones, which tend to be forgotten. The paper revolves around the views, limitation of current system and offers a dynamic biometrics, as it can be easily integrated into the existing computer security systems with minimal alteration and user intervention. The main objective is to secure using cued click point (CCP), which is one click based graphical password scheme for sequence of images and measuring, assessing humans typing rhythm, it’s based upon the human tendency to memorize graphical passwords more comfortably.
One-stop shop for software development informationAftab Iqbal
Talks about the issues which developers face while interacting with the many software repositories and the questions they usually have in their mind while search. Introduce the linked data approach to integrate the information from different software repositories.
A Novel Biometric Technique Benchmark Analysis For Selection Of Best Biometri...CSCJournals
A biometric security is a technique by means of which digital contents are protected by a cryptographic key generated from the biometric features of a person like Retina, Iris, Fingerprint, Face, Voice and so on. Normally the digital contents like documents are protected by a cryptographic key generated from a unique password. The process in irreversible, i.e the key can be generated from the password but not the vice versa. Passwords are relatively easy to hack as most of the users keep their personal information like date of birth as password and also password length has a limit as human beings cannot remember a password of significantly large length. Hence guessing the password of a user, whose significant information is available, is easier. Therefore off late lot of emphasis has been given to biometric features. Biometric features of no two people are same. For example the finger prints or the face of any two people differ. Hence if a template (alphanumeric or binary representation of features from a biometric data) is selected for the key generation than cracking them for accessing information becomes significantly difficult. But as with every advantage comes certain limitations also. The keys are not time invariant. Templates tends to change based on the data acquisition, or with time. For example the finger prints or palm prints changes with ages. Iris, retina and face features changes with change in light intensity during the acquisition phase. Fingerprint features changes with change in the orientation of the finger while scanning. In a classic authentication problem, such variability’s can be easily dealt with by keeping a threshold for the acceptance of the features. Such acceptance threshold is not applicable for the case of biometric templates. Even slightest of the variability in the templates changes the generated key, therefore causing a high false rejection rate. Hence in this work we analyze the most accepted biometric features and techniques for key generation and propose the most invariable technique in terms of data acquisition invariability. The work analyzes Iris, Face, Fingerprint and Palm prints for analysis of the biometric template generation and key generation form the templates. Further a unique benchmark analysis technique is proposed for quantifying the quality of a biometric model or features.
Certified Deep Learning Specialist (CDLS)GICTTraining
GICT Certified Deep Learning Specialist (CDLS) course will focus on the implementation of the newest libraries for implementing Deep Learning
Find Out More : https://globalicttraining.com
A survey on encryption algorithms for data securityeSAT Journals
Abstract In current world the security is more important in all fields. The data that is transferred between any must be retrieved securely. For this secure data retrieval we use cryptographic solutions. Disruption Tolerant Network (DTN) technologies have become successful solutions that permit wireless devices to speak with one another and access the guidance dependably by exploiting auxiliary storage nodes. The cryptographic solutions used for the retrieval of data are encryption algorithms. In this paper we discussed several algorithms used for the secure data retrieval in all fields. Keywords: Security, Cryptography, DTN and Encryption
Graphical Based Password for Android Phones using Keystroke Dynamics - A SurveyIJSRD
Technology has elevated to grab an important position in humans life, the best example is smartphones. They offer access to network as well as online banking transactions, where simplification of human labour affects security and user authentication, and passwords are first line of defense, it’s crucial to pick a strong password. Online banking applications currently use alphanumerical usernames and passwords for authentication, which are exposed to eves dropping, attacks, and shoulder surfing. Users often choose either easy to remember passwords, which can be easily guessed or difficult ones, which tend to be forgotten. The paper revolves around the views, limitation of current system and offers a dynamic biometrics, as it can be easily integrated into the existing computer security systems with minimal alteration and user intervention. The main objective is to secure using cued click point (CCP), which is one click based graphical password scheme for sequence of images and measuring, assessing humans typing rhythm, it’s based upon the human tendency to memorize graphical passwords more comfortably.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Lsb hiding using random approach for image watermarkingeSAT Journals
Abstract A digital image watermarking is the process of embedding an image with a secondary parameter called watermark, without deterioration in the quality of image to provide copyright protection means to provide protection for intellectual property from illegal copying. In this paper the method of nested digital image watermarking is used that means a watermark inside another watermark embedded into the cover image that is the main image. Here the Randomized LSB hiding algorithm is used for embedding one image into another as it has lesser complexity and the approach is more robust to the variations in the type of image. The blowfish algorithm is used to encrypt the watermark image before embedding into the cover image. The concept of encryption of watermark image before get embedded into the main image is used here to increase the security of the watermark image. This is because the research work is mainly focus on to get the more secured watermark by improving and enhancing the embedding capacity. Key Words: Digital image Watermarking, Randomized LSB, Blowfish, Copyright Protection
Today piracy is one of the most important issues that the owners of multimedia contents are facing now. So
it becomes necessary to protect the copyright of digital media. The new technology proposed to solve the “problem”
of enforcing the copyright of content transmitted across shared networks is Invisible Digital Watermark. It is a
technique of steganography that allow a copyright holder to insert a hidden message (invisible watermark) within
images, sound files, moving pictures and even raw text. To watermark a video it is divided into frames then extract
each bit of a frame and modify it with reference to original RGB value to embed a watermark in it. The location of
the embedded text is maintained as a key file and the frames are integrated as a video again. The slight changes in
RGB value scattered across the frame makes it impossible to visibly detect the difference when compared to original
video. To detect the piracy of video using the key file the copyright information is extracted from the watermarked
data. From the copyright information it is possible to find the source of piracy and thus necessary action can be
taken.
Keywords — hacking, authentication, cryptography, steganography, copyright.
Garbage Management using Android Smartphoneijsrd.com
Environmental pollution nowadays is a major aspect to be considered. Pollution has to be avoided and there are several ways to control it. In this paper, we propose an innovative software application, via which a user can send an alert text message and location details to the garbage/waste management department in the campus and also post the same details on the dedicated web server. This information essentially helps the respective department to take care of garbage present in the campus.
Digital watermarking knowledge is a leading edge research field and it mainly focuses on the
intellectual property rights, hides data and embedded inside an image to show authenticity or proof
of ownership, discovery and authentication of the digital media to protect the important documents.
Digital watermarking can help to verify ownership, to recognize a misappropriate person and find the
marked documents. One of the significant technological actions of the last two decades was the
attack of digital media in a complete range of everyday life aspects.
Digital data can be stored efficiently with a very high quality and it can be manipulated very
easily using computers. In addition digital data can be transmitted in a fast and inexpensive way
through data communication networks without losing quality. According to the necessary study of
digital image watermarking, the digital watermarking model consists of two modules, which are
watermark embedding module and watermark extraction and detection module.
A model for privacy-enhance federated identity managementrhoerbe1
Identity federations operating in a business or consumer context need to prevent the collection of user data across trust service providers for legal and business case reasons. Other reasons include business owners becoming increasingly aware of confidentiality risks that go beyond traditional information security, e.g., the numbers of authentications to an EDI service might provide insights into the volume of invoices, from which one could derive insider information. This presenation proposes extended technical controls supporting more strict privacy requirements, predominantly limited linkability and limited observability.
Using a hub-and-spoke federation style following the privacy-by-design principle, this reference architecture addresses the privacy controls mentioned above. Opposed to PET (privacy enhanced technologies) this model does not require advanced cryptography and fits into existing technology stacks such as WS-Trust and SAML WebSSO.
— A CAPTCHA means "Completely Automated
Public Turing test to tell Computers and Humans Apart". It is a
type of challenge-response test used in computing to determine
whether or not the user is human. CaRP is both a Captcha and a
graphical password scheme. CaRP addresses a number of
security problems altogether, such as online guessing attacks,
relay attacks, and, if combined with dual-view technologies,
shoulder-surfing attacks. Particularly, a CaRP password can be
found only probabilistically by automatic online guessing attacks,
even if the password is in the search set. CaRP also offers an
approach to address the well-known image hotspot problem in
popular graphical password systems, such as PassPoints, which
often leads to weak password choices. Thus, a variant to the
login/password scheme, using graphical scheme was introduced.
But it also suffered due to shoulder-surfing and screen dump
attacks. Thus it introduces a framework to proposed (IPAS)
Implicit Password Authentication System, which is protected to
the common attacks suffered by other authentication schemes.
masterclass de introducción a Inteligencia Artificial utilizando las APIs de Google elaborada a partir de la de Mario Ezquerro en GDG La Rioja.
Impartida dentro de las actividades de la Agenda Digital de La Rioja por AERTIC
Profile based Video segmentation system to support E-learningGihan Wikramanayake
S C Premaratne, D D Karunaratna, G N Wikramanayake, K P Hewagamage, G K A Dias (2004) "Profile Based Video Segmentation System to Support e-Learning" In:6th International Information Technology Conference, Edited by:V.K. Samaranayake et al. pp. 74-81. Infotel Lanka Society, Colombo, Sri Lanka: IITC Nov 29-Dec 1, ISBN: 955-8974-01-3
Inverted File Based Search Technique for Video Copy Retrievalijcsa
A video copy detection system is a content-based search engine focusing on Spatio-temporal features. It
aims to find whether a query video segment is a copy of video from the video database or not based on the
signature of the video. It is hard to find whether a video is a copied video or a similar video since the
features of the content are very similar from one video to the other. The main focus is to detect that the
query video is present in the video database with robustness depending on the content of video and also by
fast search of fingerprints. The Fingerprint Extraction Algorithm and Fast Search Algorithm are adopted
to achieve robust, fast, efficient and accurate video copy detection. As a first step, the Fingerprint
Extraction algorithm is employed which extracts a fingerprint through the features from the image content
of video. The images are represented as Temporally Informative Representative Images (TIRI). Then the
next step is to find the presence of copy of a query video in a video database, in which a close match of its
fingerprint in the corresponding fingerprint database is searched using inverted-file-based method.
PERFORMANCE ANALYSIS OF FINGERPRINTING EXTRACTION ALGORITHM IN VIDEO COPY DET...IJCSEIT Journal
A video fingerprint is a recognizer that is derived from a piece of video content. The video fingerprinting
methods obtain unique features of a video that differentiates one video clip from another. It aims to identify
whether a query video segment is a copy of video from the video database or not based on the signature of
the video. It is difficult to find whether a video is a copied video or a similar video, since the features of the
content are very similar from one video to the other. The main focus of this paper is to detect that the query
video is present in the video database with robustness depending on the content of video and also by fast
search of fingerprints. The Fingerprint Extraction Algorithm and Fast Search Algorithms are adopted in
this paper to achieve robust, fast, efficient and accurate video copy detection. As a first step, the
Fingerprint Extraction algorithm is employed which extracts a fingerprint through the features from the
image content of video. The images are represented as Temporally Informative Representative Images
(TIRI). Then, the second step is to find the presence of copy of a query video in a video database, in which
a close match of its fingerprint in the corresponding fingerprint database is searched using inverted-filebased
method. The proposed system is tested against various attacks like noise, brightness, contrast,
rotation and frame drop. Thus the performance of the proposed system on an average shows high true
positive rate of 98% and low false positive rate of 1.3% for different attacks.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Lsb hiding using random approach for image watermarkingeSAT Journals
Abstract A digital image watermarking is the process of embedding an image with a secondary parameter called watermark, without deterioration in the quality of image to provide copyright protection means to provide protection for intellectual property from illegal copying. In this paper the method of nested digital image watermarking is used that means a watermark inside another watermark embedded into the cover image that is the main image. Here the Randomized LSB hiding algorithm is used for embedding one image into another as it has lesser complexity and the approach is more robust to the variations in the type of image. The blowfish algorithm is used to encrypt the watermark image before embedding into the cover image. The concept of encryption of watermark image before get embedded into the main image is used here to increase the security of the watermark image. This is because the research work is mainly focus on to get the more secured watermark by improving and enhancing the embedding capacity. Key Words: Digital image Watermarking, Randomized LSB, Blowfish, Copyright Protection
Today piracy is one of the most important issues that the owners of multimedia contents are facing now. So
it becomes necessary to protect the copyright of digital media. The new technology proposed to solve the “problem”
of enforcing the copyright of content transmitted across shared networks is Invisible Digital Watermark. It is a
technique of steganography that allow a copyright holder to insert a hidden message (invisible watermark) within
images, sound files, moving pictures and even raw text. To watermark a video it is divided into frames then extract
each bit of a frame and modify it with reference to original RGB value to embed a watermark in it. The location of
the embedded text is maintained as a key file and the frames are integrated as a video again. The slight changes in
RGB value scattered across the frame makes it impossible to visibly detect the difference when compared to original
video. To detect the piracy of video using the key file the copyright information is extracted from the watermarked
data. From the copyright information it is possible to find the source of piracy and thus necessary action can be
taken.
Keywords — hacking, authentication, cryptography, steganography, copyright.
Garbage Management using Android Smartphoneijsrd.com
Environmental pollution nowadays is a major aspect to be considered. Pollution has to be avoided and there are several ways to control it. In this paper, we propose an innovative software application, via which a user can send an alert text message and location details to the garbage/waste management department in the campus and also post the same details on the dedicated web server. This information essentially helps the respective department to take care of garbage present in the campus.
Digital watermarking knowledge is a leading edge research field and it mainly focuses on the
intellectual property rights, hides data and embedded inside an image to show authenticity or proof
of ownership, discovery and authentication of the digital media to protect the important documents.
Digital watermarking can help to verify ownership, to recognize a misappropriate person and find the
marked documents. One of the significant technological actions of the last two decades was the
attack of digital media in a complete range of everyday life aspects.
Digital data can be stored efficiently with a very high quality and it can be manipulated very
easily using computers. In addition digital data can be transmitted in a fast and inexpensive way
through data communication networks without losing quality. According to the necessary study of
digital image watermarking, the digital watermarking model consists of two modules, which are
watermark embedding module and watermark extraction and detection module.
A model for privacy-enhance federated identity managementrhoerbe1
Identity federations operating in a business or consumer context need to prevent the collection of user data across trust service providers for legal and business case reasons. Other reasons include business owners becoming increasingly aware of confidentiality risks that go beyond traditional information security, e.g., the numbers of authentications to an EDI service might provide insights into the volume of invoices, from which one could derive insider information. This presenation proposes extended technical controls supporting more strict privacy requirements, predominantly limited linkability and limited observability.
Using a hub-and-spoke federation style following the privacy-by-design principle, this reference architecture addresses the privacy controls mentioned above. Opposed to PET (privacy enhanced technologies) this model does not require advanced cryptography and fits into existing technology stacks such as WS-Trust and SAML WebSSO.
— A CAPTCHA means "Completely Automated
Public Turing test to tell Computers and Humans Apart". It is a
type of challenge-response test used in computing to determine
whether or not the user is human. CaRP is both a Captcha and a
graphical password scheme. CaRP addresses a number of
security problems altogether, such as online guessing attacks,
relay attacks, and, if combined with dual-view technologies,
shoulder-surfing attacks. Particularly, a CaRP password can be
found only probabilistically by automatic online guessing attacks,
even if the password is in the search set. CaRP also offers an
approach to address the well-known image hotspot problem in
popular graphical password systems, such as PassPoints, which
often leads to weak password choices. Thus, a variant to the
login/password scheme, using graphical scheme was introduced.
But it also suffered due to shoulder-surfing and screen dump
attacks. Thus it introduces a framework to proposed (IPAS)
Implicit Password Authentication System, which is protected to
the common attacks suffered by other authentication schemes.
masterclass de introducción a Inteligencia Artificial utilizando las APIs de Google elaborada a partir de la de Mario Ezquerro en GDG La Rioja.
Impartida dentro de las actividades de la Agenda Digital de La Rioja por AERTIC
Profile based Video segmentation system to support E-learningGihan Wikramanayake
S C Premaratne, D D Karunaratna, G N Wikramanayake, K P Hewagamage, G K A Dias (2004) "Profile Based Video Segmentation System to Support e-Learning" In:6th International Information Technology Conference, Edited by:V.K. Samaranayake et al. pp. 74-81. Infotel Lanka Society, Colombo, Sri Lanka: IITC Nov 29-Dec 1, ISBN: 955-8974-01-3
Inverted File Based Search Technique for Video Copy Retrievalijcsa
A video copy detection system is a content-based search engine focusing on Spatio-temporal features. It
aims to find whether a query video segment is a copy of video from the video database or not based on the
signature of the video. It is hard to find whether a video is a copied video or a similar video since the
features of the content are very similar from one video to the other. The main focus is to detect that the
query video is present in the video database with robustness depending on the content of video and also by
fast search of fingerprints. The Fingerprint Extraction Algorithm and Fast Search Algorithm are adopted
to achieve robust, fast, efficient and accurate video copy detection. As a first step, the Fingerprint
Extraction algorithm is employed which extracts a fingerprint through the features from the image content
of video. The images are represented as Temporally Informative Representative Images (TIRI). Then the
next step is to find the presence of copy of a query video in a video database, in which a close match of its
fingerprint in the corresponding fingerprint database is searched using inverted-file-based method.
PERFORMANCE ANALYSIS OF FINGERPRINTING EXTRACTION ALGORITHM IN VIDEO COPY DET...IJCSEIT Journal
A video fingerprint is a recognizer that is derived from a piece of video content. The video fingerprinting
methods obtain unique features of a video that differentiates one video clip from another. It aims to identify
whether a query video segment is a copy of video from the video database or not based on the signature of
the video. It is difficult to find whether a video is a copied video or a similar video, since the features of the
content are very similar from one video to the other. The main focus of this paper is to detect that the query
video is present in the video database with robustness depending on the content of video and also by fast
search of fingerprints. The Fingerprint Extraction Algorithm and Fast Search Algorithms are adopted in
this paper to achieve robust, fast, efficient and accurate video copy detection. As a first step, the
Fingerprint Extraction algorithm is employed which extracts a fingerprint through the features from the
image content of video. The images are represented as Temporally Informative Representative Images
(TIRI). Then, the second step is to find the presence of copy of a query video in a video database, in which
a close match of its fingerprint in the corresponding fingerprint database is searched using inverted-filebased
method. The proposed system is tested against various attacks like noise, brightness, contrast,
rotation and frame drop. Thus the performance of the proposed system on an average shows high true
positive rate of 98% and low false positive rate of 1.3% for different attacks.
The ubiquitous and connected nature of camera loaded mobile devices has greatly estimated the value and importance of visual information they capture. Today, sending videos from camera phones uploaded by unknown users is relevant on news networks, and banking customers expect to be able to deposit checks using mobile devices. In this paper we represent Movee, a system that addresses the fundamental question of whether the visual stream exchange by a user has been captured live on a mobile device, and has not been tampered with by an adversary. Movee leverages the mobile device motion sensors and the inherent user movements during the shooting of the video. Movee exploits the observation that the movement of the scene recorded on the video stream should be related to the movement of the device simultaneously captured by the accelerometer. the last decade e-lecturing has become more and more popular. We model the distribution of correlation of temporal noise residue in a forged video as a Gaussian mixture model (GMM). We propose a twostep scheme to estimate the model parameters. Consequently, a Bayesian classifier is used to find the optimal threshold value based on the estimated parameters. Cyrus Deboo | Shubham Kshatriya | Rajat Bhat"Video Liveness Verification" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-3 , April 2018, URL: http://www.ijtsrd.com/papers/ijtsrd12772.pdf http://www.ijtsrd.com/computer-science/other/12772/video-liveness-verification/cyrus-deboo
1. .
Acknowledgments
We thank Jay F. Nunamaker, Jr., Elyse Golob, Riley McIsaac, and the
Deception Detection Research Team at CMI, University of Arizona, Tucson, AZ
MS SQL Server 2008 combines several features, including
Filestream, full-text indexing and searching, to support multimedia
data management. However, synchronizing, capturing , and indexing
multiple audio/video streams in real-time is challenging.
Performing reliable deception detection analysis on live
streams will depend on the accuracy of the anchor models and the
detection analysis engine. Low level features (color, texture, shape)
which can be automatically extracted are not adequate; semantic
feature of images convey a higher level of abstraction. Annotation
generated using MPEG-7 (Part 5) provide several benefits to
generate knowledge base for semantic features analysis, including
interoperability with standardized framework, such as RDF.
To support near real-time detection, audio/video streams
must be segmented; thus, allows each segment to be captured,
stored, and then retrieved for annotation.
Further studies are required to design yhe visual concept
models and deception detection analysis engine.
Eranna K. Guruvadoo and Christopher Clarke (Bethune-Cookman University, Daytona Beach, Florida)
University of Arizona (BORDERS) , Center for the Management of Information (CMI).
References
Angelides, M. C. , Agius, Harry; “An MPEG-7 scheme for semantic
content modeling and filtering of digital video”, Multimedia Systems
(2006) 11(4): pp 320–339.
Derrick, D. C., Elkins, a. c., Burgoon, j. k., Nunamaker Jr. j. f., and Zeng,
D. . “Border Security Credibility Assessments via Heterogeneous
Sensor Fusion”, University of Arizona, IEEE Intelligent Systems,
May/June 2010; pp 41-49.
Goularte, R., Cattelan, R. G., Camacho-Guerrero, R. J. Inácio Jr., V. T.
Pimentel, M. C. “Interactive Multimedia Annotations: Enriching and
Extending Content”. Proceedings of the 2004 ACM symposium on
Document engineering, pp: 84 – 86.
Sivrikaya, F., Yener, B. “Time Synchronization inSensor Network: A
Survey”, IEEE Networks, June 2004, pp 45-50.
Richardson, I. E., [H.264 and MPEG-4 video compression: video coding
for next generation multimedia], Wiley, 1 ed. (August 2003).
Link for:
Blender - http://www.blender.org/documentation/248PythonDoc/
Poser - http://poser.smithmicro.com/poser.html
For further information
Please contact Guruvadoo at : guruvado@cookman.edu and Christopher
Clarke at: christclarke@live.com
More information on related projects can be obtained at
http://www.borders.arizona.edu/files/reports/templates-annual.html
How it’s done?
Part 5 of MPEG-7 contains Multimedia Description Scheme(MDS)
MPEG-7 is for description of multimedia content Descriptors (D) -> basic
descriptive features of media; Description schemes (DS) (complex descriptive
units made up of DS’s and D’s
MPEG-7 essentially standardize two things:
• The description Definition Language (DDL) for scheme definition
•Using the DDL, produce a comprehensive set of media description
schemes useful for many applications
New description schemes can be created by extending the predefined set or
created from scratch
Automatic Labeling process
Goal : to create anchor models for Visual Concept
Use surrogate video/audio frames to build knowledge base
Use Shot segmentation to perform shot boundaries
Use Object segmentation; remove background; Select objects of interest
Annotation – use labels from trained visual concept models and ontology to
associate labels to objects
Build classifier
Output: XML file of annotations; XML output used for indexing
Deception Detection Research
A proof of Concept for a Data Infrastructure and 3D Avatar Control
Sensors detect 5
physiological/behavioral patterns
•Near Infrared Camera
•Gaze behavior
(saccade and gaze duration)
•Pupil dilations
• Video
•Kinesics
•Audio
•Vocalic stress
•Linguistic cues
•Identification
•RFID
•Fingerprint Reader
•Card Reader
The Deception Detection Initiative consists of multi-phase projects to evaluate
technologies and interviewing techniques that might aid human screeners to
achieve rapid, reliable, and non-invasive credibility assessment in high traffic
scenarios. The objective is to identify and evaluate those non-contact methods that
hold promise for real-time tracking of large volumes of people and determining their
physiological and psychological states in a manner that minimizes disruptions for
innocent citizenry, yet shows high sensitivity to individuals who may pose national
security risks.
Experiments have been conducted using sensor technologies, avatar kiosk,
and devices as shown below. The collection, management, and analysis of the
various data streams in real-time represent significant challenges for ongoing
research. This project demonstrates a proof of concept for a data infrastructure and
that will meet the critical need of the ongoing research projects. A secondary
component of this project investigates the control of avatar as automated agent.
Deception Detection Model Interview Equipment Layout
Avatar Kiosk – 2nd generation
Video Cameras
Laser-Doppler
Vibrometer
Thermal Camera
Blink Camera
Pulillometry Cameras
Eye-Tracking
System
Linguistics
Vocalics
Kinesics
Blood Pressure
Heart Rate
Respiration
Eyes, Ears
Forehead /Face
Blink Rate/ Frequency
Change in Blink Activity
Iris identification
Pupil Dilation
Gaze Behavior
Object Recognition
Pattern Classification
Truth or
Deception
Data Fusion Model
Issues
• No infrastructure to capture, synchronize, and index
massive data streams
• Tape storage systems; Off-line/post annotation and
processing (labor intensive)
• Minimal avatar animation
Goal
• Real-time data capture & indexing to support Near Real-
time deception detection
• Real-time automated lip-synchronization & facial animation
with text-to-speech engines/raw voice data for avatar
Tasks
• Develop proof of concept for data infrastructure
• Identify /investigate suitable rendering
engine/programming languages for avatar animation
Real- time capture & Synchronization of audio/video stream
Time code generator/receiver; IRIG-B card
VBrick's Video Encoder Appliances; Recorders; Network Video
Encoders
Real-time Capture and store multiple audio/video stream
Using Stream 5 Software with frame grabbers
Retrieve captured stream; collect metadata (for indexing); thread data
to SQL Server 2008.
Inject real time textual data synchronized with live or stored video
Segmentation of Audio/Video Streams
Hierarchical Structure
Segment streams (question number used as primary key
Next level: segmentation by frame #
Time Intervals of event of interest
MS Sql Server 2008
FILSTREAM feature for storage
Full-text Engine & Full-text index - Linguistic search more accurate
that “like” operator; IFilter, IWordBreaker, and IStemmer.
Windows server 2008 Multimedia class scheduler
Media description : technical or semantic level
Technical –Low level aspect (automatic extraction)
Semantic - conveys higher level of abstraction
Use technical to build domain ontology and semantic annotation
Semantic Content Modeling
Why? Low-level features not adequate
Knowledge base built from collection of annotated images to serve as
surrogate for the actual data stream
Object and object properties form the basis of various multimedia
specific ontology
Spatial relationship between objects
Semantic content aspects can have generic applicability since virtually
all domains require some representations of events and objects,
including relationship between them
Data Infrastructure
(a) Literature reviews of current audio/video technologies for: streams
synchronization; capture, indexing, and storage; automated labeling to create anchor
models to be used in detection engines for deception detection.
Technologies surveyed:
Common Multimedia DB - Oracle Multimedia, IBM DB2 Image Extender,
IBM Informix Data Blades, Special purpose MMDBMS, e.g. MARS, RETIN
Microsoft FILESTREAM indexing/storage
MPEG-7 (part 5) for semantic content modeling
Use of encoders fro compression and indexing
(b) Prototyping/scripting MS SQL Server 2008 for multimedia data
Avatar Animation
3D- Software – Blender (for modeling/animation/rendering)
Game Engine – Unity (to create interactive content)
Programming/scripting in Python
Create fully modeled creature
Find best ways to produce and control actions of the model
Develop animation to make creature “lifelike” including saying phrases
Use Python code to control actions
Used poser as the second software for testing
Used downloadable character
Import the character into the 3D engine
Results
Methods Used
Encoder
Annotation Manager
Segmentation
Manager
Deception/Detection
Analysis Engine
Database Output
Audio/video
stream
MPEG-7 XML file
Avatar Animation
Real-time Audio/Video Analysis
Introduction
• Characters modeled in Blender
• Animation of characters
• Control actions with Python codes
• Control animation through time-line
• Poser tested simarly
• using the NLA action strips to control
predefined actions
• Posers downloadable characters and
animations
Avatar Animation
Using Blender and Poser restrict animation to time-line
The 3D software can be used to create the character before importing
them into game engine.
Limitation on number of poly count for importing into game engine
Other game engines need to be tested for the real-time constraint the
avatar animation must meet
Anchor Models
Conclusions
Editor's Notes
This poster template is from http://www.swarthmore.edu/NatSci/cpurrin1/posteradvice.htm. It is free, free, free for non-commercial use. If you really like it, I’m always thrilled to get postcards from wherever you happen to be presenting your poster. -- Colin Purrington, Department of Biology, Swarthmore College, Swarthmore, PA 19081, USA. cpurrin1@swarthmore.edu