TUTCRIS - Tampereen teknillinen yliopisto

TUTCRIS

Active classification for human action recognition

Tutkimustuotosvertaisarvioitu

Yksityiskohdat

AlkuperäiskieliEnglanti
Otsikko2013 IEEE International Conference on Image Processing, ICIP 2013 - Proceedings
Sivut3249-3253
Sivumäärä5
DOI - pysyväislinkit
TilaJulkaistu - 2013
OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisussa
Tapahtuma2013 20th IEEE International Conference on Image Processing, ICIP 2013 - Melbourne, VIC, Austraalia
Kesto: 15 syyskuuta 201318 syyskuuta 2013

Conference

Conference2013 20th IEEE International Conference on Image Processing, ICIP 2013
MaaAustraalia
KaupunkiMelbourne, VIC
Ajanjakso15/09/1318/09/13

Tiivistelmä

In this paper, we propose a novel classification method involving two processing steps. Given a test sample, the training data residing to its neighborhood are determined. Classification is performed by a Single-hidden Layer Feedforward Neural network exploiting labeling information of the training data appearing in the test sample neighborhood and using the rest training data as unlabeled. By following this approach, the proposed classification method focuses the classification problem on the training data that are more similar to the test sample under consideration and exploits information concerning to the training set structure. Compared to both static classification exploiting all the available training data and dynamic classification involving data selection for classification, the proposed active classification method provides enhanced classification performance in two publicly available action recognition databases.

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