Human Gait Recognition Using Temporal Slices
Conference paper
Abstract
Gait along with body structure has been recognized as a potential biometric feature for identifying human beings. The spatial and temporal shape of motion of an individual is usually the same for all gait cycles and is considered to be unique to that individual. In this paper we introduce a Temporal Slice based approach for gait recognition. Temporal Slices are a set of two-dimensional images extracted along the time dimension of an image volume. They encode a rich set of visual patterns for similarity measure and have been widely used for motion detection. We show that the features obtained from tensor histogram of these temporal slices can be efficiently used as gait features for recognition of human beings.
Keywords
Gait biometrics Temporal Slices Tensor Histogram Multiclass SVM Download
to read the full conference paper text
References
- 1.Wang, L., Tan, T., Ning, H., Hu, W.: Automatic Gait Recognition Based on Statistical Shape Analysis. IEEE Transactions on Image Processing 12(9), 1120–1131 (2003)CrossRefMathSciNetGoogle Scholar
- 2.Wang, L., Tan, T., Ning, H., Hu, W.: Silhouette Analysis Based Gait Recognition for Human Identification. IEEE Transactions on Pattern Analysis and Machine Intelligence 25(12), 1505–1518 (2003)CrossRefGoogle Scholar
- 3.Liu, Z., Sarkar, S.: Improved Gait Recognition by Gait Dynamics Normalization. IEEE Transactions on Pattern Analysis and Machine Intelligence 28(6), 863–876 (2006)CrossRefGoogle Scholar
- 4.Kale, A., Sundaresan, A., Rajagopalan, A.N., Cuntoor, N.P., Roy-Chowdhury, A.K., Kruger, V., Chellappa, R.: Identification of Humans Using Gait. IEEE Transactions on Image Processing 13, 1163–1173 (2004)CrossRefGoogle Scholar
- 5.Han, J., Bhanu, B.: Individual Recognition using Gait Energy Image. IEEE Transactions of Pattern Recognition and Machine Intelligence 28(2), 316–322 (2006)CrossRefGoogle Scholar
- 6.Bolgouris, N.V., Plataniotis, K.N., Hatzinakos, D.: Gait Recognition using Dynamic Time Warping. In: Sixth IEEE Workshop on Multimedia Signal Processing, pp. 969–979 (2004)Google Scholar
- 7.Ngo, C.W., Pong, T.C., Zhang, H.J.: On Clustering and Retrieval of Video Shots through Temporal Slice Analysis. IEEE Transactions on Multimedia 4(4), 446–458 (2002)CrossRefGoogle Scholar
- 8.Sagawa, R., Makihara, Y., Echigo, T., Yagi, Y.: Matching Gait Image Sequences in the Frequency Domain for Tracking People at a Distance. In: Proceedings of 7th Asian Conference on Computer Vision, vol. 2, pp. 141–150 (2006)Google Scholar
- 9.Gross, R., Shi, J.: The CMU Motion of Body (MoBo) Database, Tech. Report CMU-RI-TR-01-18, Robotics Institute, Carnegie Mellon University (2001)Google Scholar
- 10.Sarkar, S., Phillips, P.J., Liu, Z., Robledo-Vega, I., Grother, P., Bowyer, K.W.: The Human ID Gait Challenge Problem: Data Sets, Performance, and Analysis. IEEE Transactions on Pattern Analysis and Machine Intelligence 27(2), 162–177 (2005)CrossRefGoogle Scholar
- 11.Collins, R., Gross, R., Shi, J.: Silhouette-Based Human Identification from Body Shape and Gait. In: Proceedings of International Conference on Automatic Face and Gesture Recognition, pp. 366–371 (2002)Google Scholar
- 12.Kale, A., Rajagopalan, A., Cuntoor, N., Krueger, V.: Gait-Based Recognition of Humans using Continuous HMMs. In: Proceedings of International Conference on Automatic Face and Gesture Recognition, pp. 321–326 (May 2002)Google Scholar
- 13.Ben Abdelkader, C., Cutler, R., Davis, L.: Motion-Based Recognition of People in Eigengait Space. In: Proceedings of International Conference on Automatic Face and Gesture Recognition, pp. 267–272 (2002)Google Scholar
- 14.Lee, L., Grimson, W.: Gait Analysis for Recognition and Classification. In: Proceedings of International Conference on Automatic Face and Gesture Recognition, pp. 155–162 (2002)Google Scholar
- 15.Crammer, K., Singer, Y.: On the Algorithmic Implementation of Multiclass kernel based Vector Machine. Journal of Machine learning Research, 265–292 (2001)Google Scholar
Copyright information
© Springer-Verlag Berlin Heidelberg 2007