Gait recognition using static, activity-specific parameters

A gait-recognition technique that recovers static body and stride parameters of subjects as they walk is presented. This approach is an example of an activity-specific biometric: a method of extracting identifying properties of an individual or of an individual's behavior that is applicable only when a person is performing that specific action. To evaluate our parameters, we derive an expected confusion metric (related to mutual information), as opposed to reporting a percent correct with a limited database. This metric predicts how well a given feature vector will filter identity in a large population. We test the utility of a variety of body and stride parameters recovered in different viewing conditions on a database consisting of 15 to 20 subjects walking at both an angled and frontal-parallel view with respect to the camera, both indoors and out. We also analyze motion-capture data of the subjects to discover whether confusion in the parameters is inherently a physical or a visual measurement error property.

[1]  Stefan Carlsson.  Recognizing Walking People , 2000, ECCV.

[2]  J. Little,et al.  Recognizing People by Their Gait: The Shape of Motion , 1998 .

[3]  S. Stevenage,et al.  Visual analysis of gait as a cue to identity , 1999 .

[4]  M. Nixon,et al.  Human gait recognition in canonical space using temporal templates , 1999 .

[5]  J. Cutting,et al.  Recognizing friends by their walk: Gait perception without familiarity cues , 1977 .

[6]  J. Cutting,et al.  Recognizing the sex of a walker from a dynamic point-light display , 1977 .

[7]  Aaron F. Bobick,et al.  A Multi-view Method for Gait Recognition Using Static Body Parameters , 2001, AVBPA.

[8]  J. Hanley,et al.  The meaning and use of the area under a receiver operating characteristic (ROC) curve. , 1982, Radiology.

[9]  Larry S. Davis,et al.  W/sup 4/: Who? When? Where? What? A real time system for detecting and tracking people , 1998, Proceedings Third IEEE International Conference on Automatic Face and Gesture Recognition.

[10]  M. Nixon,et al.  Automatic Gait Recognition via Model-Based Evidence Gathering , 1999 .

[11]  Hiroshi Murase,et al.  Moving object recognition in eigenspace representation: gait analysis and lip reading , 1996, Pattern Recognit. Lett..

[12]  Larry S. Davis,et al.  A Robust Background Subtraction and Shadow Detection , 1999 .

[13]  Edward H. Adelson,et al.  Analyzing and recognizing walking figures in XYT , 1994, 1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.