Gait Analysis using Independent Components of image motion

We propose a novel approach to gait analysis using the independent components of motion. Our motion representation uses the amount of translation in small image patches. For each subject in the training set, several short image sequences are selected at random. Spatiotemporal independent component analysis (stICA) estimates independent components (ICs) of the training sequences. Given an unknown subject, we compute stIC coefficients for all image subsequences. These coefficients are compared with the training set using the cosine similarity measure. We demonstrate feasibility by using the nearest neighbor to classify the gender of a subject.

[1]  W. Eric L. Grimson,et al.  Gait analysis for recognition and classification , 2002, Proceedings of Fifth IEEE International Conference on Automatic Face Gesture Recognition.

[2]  A. B. Drought,et al.  WALKING PATTERNS OF NORMAL MEN. , 1964, The Journal of bone and joint surgery. American volume.

[3]  Erkki Oja,et al.  A fast algorithm for estimating overcomplete ICA bases for image windows , 1999, IJCNN'99. International Joint Conference on Neural Networks. Proceedings (Cat. No.99CH36339).

[4]  Harry Wechsler,et al.  Reliable face recognition methods - system design, implementation and evaluation , 2006 .

[5]  Terrence J. Sejnowski,et al.  An Information-Maximization Approach to Blind Separation and Blind Deconvolution , 1995, Neural Computation.

[6]  Sudeep Sarkar,et al.  The humanID gait challenge problem: data sets, performance, and analysis , 2005, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[7]  Larry S. Davis,et al.  Person identification using automatic height and stride estimation , 2002, Object recognition supported by user interaction for service robots.

[8]  Dimitris N. Metaxas,et al.  Human Gait Recognition , 2004, 2004 Conference on Computer Vision and Pattern Recognition Workshop.

[9]  Bernd Jähne,et al.  Digital Image Processing: Concepts, Algorithms, and Scientific Applications , 1991 .

[10]  Bir Bhanu,et al.  Individual recognition using gait energy image , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[11]  Dimitris N. Metaxas,et al.  Human gait recognition at sagittal plane , 2007, Image Vis. Comput..

[12]  Larry S. Davis,et al.  Stride and cadence as a biometric in automatic person identification and verification , 2002, Proceedings of Fifth IEEE International Conference on Automatic Face Gesture Recognition.

[13]  Mark S. Nixon,et al.  On a Large Sequence-Based Human Gait Database , 2004 .

[14]  Sudeep Sarkar,et al.  Improved gait recognition by gait dynamics normalization , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.

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

[16]  Aapo Hyvärinen,et al.  Fast and robust fixed-point algorithms for independent component analysis , 1999, IEEE Trans. Neural Networks.

[17]  ChewYean Yam,et al.  On the relationship of human walking and running: automatic person identification by gait , 2002, Object recognition supported by user interaction for service robots.

[18]  James W. Davis,et al.  The Recognition of Human Movement Using Temporal Templates , 2001, IEEE Trans. Pattern Anal. Mach. Intell..

[19]  T D Albright,et al.  Visual motion perception. , 1995, Proceedings of the National Academy of Sciences of the United States of America.

[20]  M P Murray,et al.  COMPARISON OF FREE AND FAST SPEED WALKING PATTERNS OF NORMAL MEN , 1966, American journal of physical medicine.

[21]  Erkki Oja,et al.  Independent component analysis: algorithms and applications , 2000, Neural Networks.

[22]  Bruce A. Draper,et al.  Recognizing faces with PCA and ICA , 2003, Comput. Vis. Image Underst..

[23]  Mark S. Nixon,et al.  Gender Classification in Human Gait Using Support Vector Machine , 2005, ACIVS.

[24]  Yanxi Liu,et al.  Shape Variation-Based Frieze Pattern for Robust Gait Recognition , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.