Title :
Two-Point Gait: Decoupling Gait from Body Shape
Author :
Lombardi, Stephen ; Nishino, K. ; Makihara, Yasushi ; Yagi, Yasushi
Author_Institution :
Drexel Univ., Philadelphia, PA, USA
Abstract :
Human gait modeling (e.g., for person identification) largely relies on image-based representations that muddle gait with body shape. Silhouettes, for instance, inherently entangle body shape and gait. For gait analysis and recognition, decoupling these two factors is desirable. Most important, once decoupled, they can be combined for the task at hand, but not if left entangled in the first place. In this paper, we introduce Two-Point Gait, a gait representation that encodes the limb motions regardless of the body shape. Two-Point Gait is directly computed on the image sequence based on the two point statistics of optical flow fields. We demonstrate its use for exploring the space of human gait and gait recognition under large clothing variation. The results show that we can achieve state-of-the-art person recognition accuracy on a challenging dataset.
Keywords :
gait analysis; image representation; image sequences; shape recognition; body shape; decoupling gait; gait analysis; gait recognition; human gait modeling; image sequence; image-based representations; large clothing variation; limb motions; muddle gait; optical flow fields; person recognition accuracy; silhouettes; two-point gait; Adaptive optics; Clothing; Graphical models; Optical imaging; Robustness; Shape; Vectors; Gait Recognition; Gait Representation; Human Gait; Two-Point Gait; Two-Point Statistics;
Conference_Titel :
Computer Vision (ICCV), 2013 IEEE International Conference on
Conference_Location :
Sydney, VIC
DOI :
10.1109/ICCV.2013.133