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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Zongyi Liu Sarkar, S. |
| Copyright Year | 2004 |
| Description | Author affiliation: Comput. Sci. & Eng., South Florida Univ., Tampa, FL, USA (Zongyi Liu; Sarkar, S.) |
| Abstract | We present a robust representation for gait recognition that is compact, easy to construct, and affords efficient matching. Instead of a time series based representation comprising of a sequence of raw silhouette frames or of features extracted therein, as has been the practice, we simply align and average the silhouettes over one gait cycle. We then base recognition on the Euclidean distance between these averaged silhouette representations. We show, using the recently formulated gait challenge problem (www.gaitchallenge.org), that the improvement in execution time is 30 times while possessing recognition power that is comparable to the gait baseline algorithm, which is becoming the comparison standard in gait recognition. Experiments with portions of the average silhouette representation show that recognition power is not entirely derived from upper body shape, rather the dynamics of the legs also contribute equally to recognition. However, this study does raise intriguing doubts about the need for accurate shape and dynamics representations for gait recognition. |
| Starting Page | 211 |
| Ending Page | 214 |
| File Size | 293014 |
| Page Count | 4 |
| File Format | |
| ISBN | 0769521282 |
| ISSN | 10514651 |
| DOI | 10.1109/ICPR.2004.1333741 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2004-08-26 |
| Publisher Place | UK |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Shape Robustness Feature extraction Humans Computer science Euclidean distance Leg Displays Principal component analysis Trajectory |
| Content Type | Text |
| Resource Type | Article |
| Subject | Computer Vision and Pattern Recognition |
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