We are interested in parsing video for postproduction and archiving applications. In particular, we are developing automatic systems for producing frame-accurate descriptions of shot boundaries, frame-approximate descriptions of camera moves, shot-by-shot descriptions of framings and groupings, and a framework for semantic analysis of content. We are also developing algorithms to provide rich static visualizations of shots -- reverse storyboards -- that allow the story of the shot to be told economically and unambiguously.
At the lowest level we use a real-time mosaicing method called Simplex Adapted Mesh (SAM) [1] that estimates frame-to-frame projective transforms robustly. This is applied within a causal dual-mosaic framework [2] that allows the full shot mosaic to be built without revisiting inaccurate interframe estimates. SAM was first realized in a system for real-time interactive image mosaicing.
In research on automated movie analysis, we have developed an Automated Shot Analysis Program (ASAP) that parses movies in a way that is useful for people in the production industry. Because its underlying technology is SAM ASAP has no problem handling black-and-white footage, cartoons, or any other kind of source material.
The SALSA project (see separate page) is a semi-automated extension to ASAP suitable for use in postproduction and archiving
We are continuing to research reverse storyboarding methods [3][4] for video summarization. This work, done in collaboration with Bob Dony of the University of Guelph, has yielded visualizations that combine storyboard metaphors like onion skins and streak lines with framings and arrows. The top example here shows a relatively simple shot with object and camera motion in the same direction. The bottom example is much more complicated with several people moving in different ways within a panning shot.


[1] J A Robinson. A Simplex-Based Projective Transform Estimator. Visual Information Engineering (VIE), Guildford, pp 290-293, July, 2003. PDF
[2] J A Robinson. Collaborative Vision and Interactive Mosaicing. Vision, Video and Graphics (VVG) 2003 , Bath, July, 2003. PDF
[3] R D Dony, J W Mateer, J A Robinson. Techniques for Automated Reverse Storyboarding, IEE Journal of Vision, Image and Signal Processing Vol 152, No 4, pp 425-436, 2005.
[4] R D Dony, J W Mateer, J A Robinson, M G Day, Iconic versus Naturalistic Motion Cues in Automated Reverse Storyboarding, 2nd IEE European Conference on Visual Media Production (CVMP) 2005, pp 17-25, London, November 2005.