Human Action Recognition Using Ordinal Measure of Accumulated Motion

Cited 16 time in webofscience Cited 0 time in scopus
  • Hit : 281
  • Download : 383
This paper presents a method for recognizing human actions from a single query action video. We propose an action recognition scheme based on the ordinal measure of accumulated motion, which is robust to variations of appearances. To this end, we first define the accumulated motion image (AMI) using image differences. Then the AMI of the query action video is resized to a N x N subimage by intensity averaging and a rank matrix is generated by ordering the sample values in the sub-image. By computing the distances from the rank matrix of the query action video to the rank matrices of all local windows in the target video, local windows close to the query action are detected as candidates. To find the best match among the candidates, their energy histograms, which are obtained by projecting AMI values in horizontal and vertical directions, respectively, are compared with those of the query action video. The proposed method does not require any preprocessing task such as learning and segmentation. To justify the efficiency and robustness of our approach, the experiments are conducted on various datasets.
Publisher
HINDAWI PUBLISHING CORPORATION
Issue Date
2010
Language
English
Article Type
Article
Keywords

TEMPLATES

Citation

EURASIP JOURNAL ON ADVANCES IN SIGNAL PROCESSING

ISSN
1687-6172
DOI
10.1155/2010/219190
URI
http://hdl.handle.net/10203/99110
Appears in Collection
EE-Journal Papers(저널논문)
Files in This Item
57093.pdf(3.2 MB)Download
This item is cited by other documents in WoS
⊙ Detail Information in WoSⓡ Click to see webofscience_button
⊙ Cited 16 items in WoS Click to see citing articles in records_button

qr_code

  • mendeley

    citeulike


rss_1.0 rss_2.0 atom_1.0