Three-way auto-correlation approach to motion recognition

Pattern Recognition Letters

Volumn 30, Issue 3, 2009, Pages 212-221

  Kobayashi, Takumi ^a   Otsu, Nobuyuki ^a  

^a NATIONAL INSTITUTE OF ADVANCED INDUSTRIAL SCIENCE AND TECHNOLOGY AIST   (Japan)

Author keywords

Gait recognition; Gesture recognition; Local auto correlation; Motion feature extraction; Three way data analysis

Indexed keywords

CORRELATION METHODS; FEATURE EXTRACTION; GAIT ANALYSIS;

COMPUTATIONAL COSTS; FEATURE EXTRACTION METHODS; GAIT RECOGNITION; GAIT RECOGNITIONS; GEOMETRIC FEATURES; IMAGE SEQUENCES; LARGE DATA SETS; LOCAL AUTO-CORRELATION; MOTION FEATURE EXTRACTION; MOTION IMAGES; MOTION RECOGNITIONS; PRIORI KNOWLEDGES; REAL TIMES; SPATIO TEMPORALS; THREE-WAY DATA ANALYSIS;

GESTURE RECOGNITION;

EID: 57249088954     PISSN: 01678655     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.patrec.2008.09.006     Document Type: Article

References (24)

1. Cutting J., and Kozlowski L. Recognizing friends by their walk: Gait perception without familiarity cues. Bull. Psychonomic Soc. 9 (1977) 353-356
2. Dollar, P., Rabaud, V., Cottrell, G., Belongie, S., 2005. Behavior recognition via sparse spatio-temporal features. In: VS-PETS, pp. 65-72.
3. Hayamizu, S., Hasegawa, O., Itou, K., Sakaue, K., Tanaka, K., Nagaya, S., Nakazawa, M., Endoh, T., Togawa, F., Sakamoto, K., Yamamoto, K., 1996. RWC multimodal database for interactions by integration of spoken language and visual information. In: Internat. Conf. on Spoken Language Processing, pp. 2171-2174.
4. Ishihara, T., Otsu, N., 2004. Gesture recognition using auto-regressive coefficients of higher-order local auto-correlation features. In: Internat. Conf. on Automatic Face and Gesture Recognition, pp. 583-588.
5. Iwata, K., Satoh, Y., Kobayashi, T., Yoda, I., Otsu, N., 2007. Application of the unusual motion detection using CHLAC to the video surveillance. In: Internat. Conf. on Neural Information Processing.
6. Jhuang, H., Serre, T., Wolf, L., Poggio, T., 2007. A biologically inspired system for action recognition. In: Internat. Conf. on Computer Vision.
7. Johansson G. Visual perception of biological motion and a model for its analysis. Percept. Psychophys. 14 (1973) 201-211
8. Kim, T.K., Wong, S.F., Cipolla, R., 2007. Tensor canonical correlation analysis for action classification. In: Internat. Conf. on Computer Vision and Pattern Recognition, pp. 1-8.
9. Kobayashi, T., Otsu, N., 2004. Action and simultaneous multiple-person identification using cubic higher-order local auto-correlation. In: Internat. Conf. on Pattern Recognition, pp. 741-744.
10. Kobayashi, T., Otsu, N., 2006. A three-way auto-correlation based approach to human identification by gait. In: IEEE Workshop on Visual Surveillance, pp. 185-192.
11. Laptev I. On space-time interest points. Internat. J. Comput. Vision 64 (2005) 107-123
12. Lee, L., Dalley, G., Tieu, K., 2003. Learning pedestrian models for silhouette refinement. In: Internat. Conf. on Computer Vision, pp. 663-670.
13. Nixon M., and Carter J. Automatic recognition by gait. Proc. IEEE 94 (2006) 2013-2024
14. Niyogi, S., Adelson, E., 1994. Analyzing and recognizing walking figures in xyt. In: IEEE Conf. on Computer Vision and Pattern Recognition, pp. 469-474.
15. Otsu N. A threshold selection method from gray-level histograms. Systems Man Cybernet. 9 (1979) 62-82
16. Otsu, N., Kurita, T., 1988. A new scheme for practical flexible and intelligent vision systems. In: IAPR Workshop on Computer Vision, pp. 431-435.
17. Raytchev B., Hasegawa O., and Otsu N. User-independent online gesture recognition by relative motion extraction. Pattern Recognition Lett. 21 (2000) 69-82
18. Sarker S., Philips P., Liu Z., Vega I.R., Grother P., and Bowyer K. The humanID gait challenge problem: Data sets, performance, and analysis. Pattern Anal. Machine Intell. 27 (2005) 162-177
19. Sivic, J., Zisserman, A., 2003. Video google: A text retrieval approach to object matching in videos. In: Internat. Conf. on Computer Vision, pp. 1470-1477.
20. Sundaresan, A., Chowdhury, A., Chellappa, R., 2003. A hidden markov model based framework for recognition of humans from gait sequences. In: Internat. Conf. on Image Processing, pp. 93-96.
21. Tolliver, D., Collins, T., 2003. Gait shape estimation for identification. In: Internat. Conf. on Audio- and Video-based Biometric Person Authentication, pp. 734-742.
22. Veres, G., Gordon, L., Carter, J., Nixon, M., 2004. What image information is important in silhouette-based gait recognition? In: Internat. Conf. on Computer Vision and Pattern Recognition, pp. 776-782.
23. Wang L., Tan T., Ning H., and Hu W. Silhouette analysis-based gait recognition for human identification. Pattern Anal. Machine Intell. 25 (2003) 1505-1518
24. Wilson A.D., and Bobick A.F. Parametric hidden markov models for gesture recognition. Pattern Anal. Machine Intell. 21 (1999) 884-900