Bilkent University
Department of Computer Engineering


A Multi Scale Motion Saliency Method for Keyframe Extraction from Motion Capture Sequences


Cihan Halit
MSc. Student
Computer Engineering Department
Bilkent University

Motion capture is an increasingly popular animation technique; however data acquired by motion capture can become substantial. This makes it difficult to use motion capture data in a number of applications, such as motion editing, motion understanding, automatic motion summarization, motion thumbnail generation, or motion database search and retrieval.

To overcome this limitation, we propose an automatic approach to extract keyframes from a motion capture sequence. We treat the input sequence as motion curves, and obtain the most salient parts of these curves using a new proposed metric, called 'motion saliency'. The system selects the curves to be analyzed by a dimension reduction technique, Principal Component Analysis. We then apply frame reduction techniques to extract the most important frames as keyframes of the motion. With this approach, around 8% of the frames are selected to be keyframes for motion capture sequences. We have quantified our results both mathematically and through user tests.


DATE: 14 December, 2010, Tuesday @ 11:00
PLACE: FADA Dean's Office, Meeting Room