About cookies on this site Our websites require some cookies to function properly (required). In addition, other cookies may be used with your consent to analyze site usage, improve the user experience and for advertising. For more information, please review your options. By visiting our website, you agree to our processing of information as described in IBM’sprivacy statement. To provide a smooth navigation, your cookie preferences will be shared across the IBM web domains listed here.
Publication
ICPR 2008
Conference paper
Segmenting actions in velocity curve space
Abstract
Reliable segmentation of actions performed by objects, is critical to the understanding of semantic content in a video. Deciding which portion of object motion sequence is a distinct action unit, however, is often difficult, even for humans. We seem to hierarchically compose actions by noting characteristic changes in the nature of motion. This paper present an action segmentation algorithm that mimics these characteristics of action perception. Specifically, we show that significant curvature changes in the spatiotemporal curve formed from average velocity of the object, represent action boundaries. A hierarchical description of action is generated using a scale-space representation of this velocity curve. A method of automatic scale selection is also proposed to enable an optimal data-driven action segmentation. The technique is extensively evaluated on several different action types and comparison with human judgment of segments is reported. © 2002 IEEE.