A descriptor combining MHI and PCOG for human motion classification

Ling Shao, Ling Ji

Research output: Contribution to conferencePaper

7 Citations (Scopus)

Abstract

The performance of human motion classification and recognition systems is highly dependent on the distinctiveness and robustness of the feature descriptor. In this paper, a new descriptor containing motion, shape and spatial layout information is proposed, therefore it is more effective for action modeling and is suitable for detecting and recognizing a variety of actions. Experiments show that the proposed descriptor outperforms other existing methods, such as Moment Invariants and Histogram of Oriented Gradients, on recognizing human motions in an indoor environment with a stationary camera.
Original languageEnglish
DOIs
Publication statusPublished - Jul 2010
EventCIVR 2010 - ACM International Conference on Image and Video Retrieval - Xi'an, China
Duration: 1 Jul 2010 → …

Conference

ConferenceCIVR 2010 - ACM International Conference on Image and Video Retrieval
Period1/07/10 → …

Fingerprint

Dive into the research topics of 'A descriptor combining MHI and PCOG for human motion classification'. Together they form a unique fingerprint.

Cite this