{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,7,7]],"date-time":"2024-07-07T11:51:04Z","timestamp":1720353064338},"reference-count":4,"publisher":"World Scientific Pub Co Pte Lt","issue":"02","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. Semantic Computing"],"published-print":{"date-parts":[[2015,6]]},"abstract":"<jats:p> Human interaction recognition has been widely studied because it has great scientific importance and many potential practical applications. However, recognizing human interactions is also very challenging especially in realistic environments where the background is dynamic or has varying lighting conditions. Most existing methods rely on either spatio-temporal local features (i.e. SIFT) or human poses, or human joints to model human interactions. As a result, they are not fully unsupervised processes because they require either hand-designed features or human detection results. Motivated by the recent success of deep learning networks, we investigate a three-layer convolutional network which uses the Independent Subspace Analysis (ISA) algorithm to learn hierarchical invariant features from videos. Using the invariant features learned by the ISA, we build a bag-of-features (BOF) model to recognize human interactions. We also evaluate the performance of our approach and the effectiveness of hierarchical invariant features on video sequences of the UT-Interaction dataset which contain both interacting persons and irrelevant pedestrians in the scenes. The dataset imposes several challenging factors including moving backgrounds, clutter scenes, scales and camera jitters. Experimental results show that our three-layer convolutional ISA network is able to learn features which are effective to represent complex activities such as human interactions in realistic environments. <\/jats:p>","DOI":"10.1142\/s1793351x15400024","type":"journal-article","created":{"date-parts":[[2015,10,7]],"date-time":"2015-10-07T02:32:22Z","timestamp":1444185142000},"page":"169-191","source":"Crossref","is-referenced-by-count":2,"title":["Human Interaction Recognition Using Hierarchical Invariant Features"],"prefix":"10.1142","volume":"09","author":[{"given":"Ngoc","family":"Nguyen","sequence":"first","affiliation":[{"name":"School of Information Science, Japan Advanced Institute of Science and Technology, Nomi, Ishikawa 923-1292, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Atsuo","family":"Yoshitaka","sequence":"additional","affiliation":[{"name":"School of Information Science, Japan Advanced Institute of Science and Technology, Nomi, Ishikawa 923-1292, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"219","published-online":{"date-parts":[[2015,10,6]]},"reference":[{"key":"rf9","author":"Sefidgar Y. S.","year":"2015","journal-title":"Computer Vision and Image Understanding"},{"key":"rf27","volume-title":"Springer","author":"Hyvarinen A.","year":"2009"},{"key":"rf29","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-013-0677-1"},{"key":"rf31","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-007-0075-7"}],"container-title":["International Journal of Semantic Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.worldscientific.com\/doi\/pdf\/10.1142\/S1793351X15400024","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,8,7]],"date-time":"2019-08-07T14:51:50Z","timestamp":1565189510000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.worldscientific.com\/doi\/abs\/10.1142\/S1793351X15400024"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2015,6]]},"references-count":4,"journal-issue":{"issue":"02","published-online":{"date-parts":[[2015,10,6]]},"published-print":{"date-parts":[[2015,6]]}},"alternative-id":["10.1142\/S1793351X15400024"],"URL":"https:\/\/doi.org\/10.1142\/s1793351x15400024","relation":{},"ISSN":["1793-351X","1793-7108"],"issn-type":[{"value":"1793-351X","type":"print"},{"value":"1793-7108","type":"electronic"}],"subject":[],"published":{"date-parts":[[2015,6]]}}}