Video Browsing By Direct Manipulation - Draft 1

Video Browsing by Direct Manipulation Pierre Dragicevic, Gonzato Ramos, Jacobo Bibliowicz, Derek Nowrouzezahrai, Ravin Balakrishman, Karan Singh User Interface Design 646 Presented by Vashira Ravipanich 5171439021

Introduction • All video players use “seeker bar” to control user interaction • What if you can directly dragging in the movie?

Introduction • This paper presents a method for browsing videos by “directly dragging” their content • Automatically extracting motion data • Relative Flow Dragging

Why Direct Manipulation? • Input ~ Output • Time V.S. Space • Both are complementary NOT rival Input like ﬁnger move = Output like mouse movement Time = seeker Bar, Space = Direct Manipulation

How does it works? • Videos = sequence of multiple pictures (frame) • Extract object(s) movement Call “Trajectory Extraction” • Construct “hint path”

Relative Flow Dragging • Directness Directness => user input lang == generated output • Matching gesture with motion 2D = map 3D = scaling object, rotating object

Type of dragging • Curvilinear Dragging • Flow Dragging • Relative Dragging

Direct Manipulation Video Player - DIMP

Background Stabilization

Position Feedback

Trajectory Extraction • Computer Vision Approaches • Object Tracking - object on video sequence - motion capture, surveillance • Optical Flow - whole picture, calculate pixels - video compression • Optical Flow is better for general video player

Curvilinear Dragging Design

Proposed Solutions • 3D Distance Method • (x, y, z) where z is arc-length distance from the curve origin

Limitations • Video with back-and-forth movement, i.e a couple dancing tango • DIfﬁcult to visualize path clearly

Evaluation • User Study • 6 males, 10 females • 18 - 44 years old • Test with 2 videos with given objectives • Offer both seeker bar and relative ﬂow dragging • Which one user comfortable with the most?

Quantitative Results

Previous work on Video Browsing • Non-Linear Video Browsing - Segment of difference importance - Estimating motion activity • Visual Summaries - Generate mosaic from key frames • Content-Based Video Retrieval

Conclusion & Future Work • New way of browsing videos using direct manipulation • Appealing to touch-input handheld. iPhone, Pocket PC. • Interactive Learning Environments.

References 1. Accot, J. and Zhai, S. (1997). Beyond Fitts' law: mod- 11. Dragicevic, P., Huot, S. and Huot, S. (2002). SpiraC- els for trajectory-based HCI tasks. CHI. p. 295-302. lock: a continuous and non-intrusive display for up- 2. Appert, C. and Fekete, J. (2006). OrthoZoom scroller: coming events. CHI Extended Abstracts. p. 604-605. 1D Multi-Scale Navigation. CHI. P. 21-30. 12. Goldman, D.B., Curless, B., Salesin, D. and Seitz, S.M. 3. Autodesk Maya. http://www.autodesk.com/ (2006). Schematic storyboarding for video visualization 4. Baudel, T., Fitzmaurice, G., Buxton, W., Kurtenbach, and editing. SIGGRAPH. p. 862-871. G., Tappen, C. and Liepa, P. (2002). Drawing system 13. Guimbretière, F. (2000). FlowMenu: combining com- using design guides. US Patent # 6,377,240. mand, text, and data entry. UIST. p. 213-216. 5. Beauchemin, S.S. and Barron, J.L. (1995). The compu- 14. Hölzl, R. (1996). How does ‘dragging’ affect the learn- tation of optical ﬂow. ACM Computing Surveys, 27(3). ing of geometry? International Journal of Computers p. 433-467. for Mathematical Learning, 1(2). p. 169-187. 6. Beaudouin-Lafon, M. (2000). Instrumental Interaction: 15. Hutchins, E.L., Hollan, J.D. and Norman, D.A. (1987). An interaction model for designing post-WIMP user in- Direct manipulation interfaces. In Human-Computer interfaces. CHI. p. 446-453. teraction: A Multidisciplinary Approach. R. M. Baeck- 7. Beaudouin-Lafon, M. (2001). Novel interaction tech- er, Ed. Morgan Kaufmann. p. 468-470. niques for overlapping windows. UIST. p. 153-154. 16. Irani, M., Anadan, P. and Hsu, H. (1995). Mosaic based 8. Bezerianos, A., Dragicevic, P. and Balakrishnan, R. representations of video sequences and their applica- (2006). Mnemonic rendering: an image-based approach tions. Intl. Conference on Computer Vision. p. 605-611. for exposing hidden changes in dynamic displays. 17. Kim, C. and Hwang, J. (2002). Fast and automatic UIST. p. 159-168. video object segmentation and tracking for content- 9. Buxton, W. (1986). There's more to interaction than based applications. IEEE Trans. Circuits and Systems meets the eye: some issues in manual input. In User for Video Technology, 12. p. 122-129. Centered System Design: New Perspectives on Human- 18. Kimber D., Dunnigan, T., Girgensohn, A., Shipman, F., Computer Interaction. Lawrence Erlbaum. p. 19-337. Turner, T. and Yang, T. (2007). Trailblazing: Video 10. Cheng,Y. (1995). Mean shift, mode seeking, and clus- playback control by direct object manipulation. ICME. tering. IEEE Transactions on Pattern Analysis and Ma- p. 1015-1018. chine Intelligence, 17(8). p. 790-799. 19. Li, F.C., Gupta, A., Sanocki, E., He, L. and Rui, Y.

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Video Browsing By Direct Manipulation - Draft 1

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