Comparing Different Template Features for Recognizing People by their Gait

To recognize people by their gait from a sequence of images, we have proposed a statistical approach which combined eigenspace transformation (EST) with canonical space transformation (CST) for feature transformation of spatial templates. This approach is used to reduce data dimensionality and to optimize the class separability of different gait sequences simultaneously. Good recognition rates have been achieved. Here, we incorporate temporal information from optical flows into three kinds of temporal templates and use them as features for gait recognition in addition to the spatial templates. The recognition performance for four kinds of template features has been evaluated in this paper. Experimental results show that spatial templates, horizontal-flow templates and the combined horizontal-flow and vertical-flow templates are better than vertical-flow templates for gait recognition.

• Type: Conference
• Year: 1998
• Where: BMVC
• Authors: Ping S. Huang, Chris J. Harris, Mark S. Nixon
• Keywords: BMVC 1998, Computer Vision, Gait, Gait Recognition, Spatial Templates