Action recognition in videos is a relevant and challenging task of automatic semantic video analysis. Most successful approaches exploit local space-time descriptors. These descriptors are usually carefully engineered in order to obtain feature invariance to photometric and geometric variations. The main drawback of space-time descriptors is high dimensionality and efficiency. In this paper we propose a novel descriptor based on 3D Zernike moments computed for space-time patches. Moments are by construction not redundant and therefore optimal for compactness. Given the hierarchical structure of our descriptor we propose a novel similarity procedure that exploits this structure comparing features as pyramids. The approach is tested on a public dataset and compared with state-of-the art descriptors.

Space-time Zernike Moments and Pyramid Kernel Descriptors for Action Classification / L., Costantini; L., Seidenari; Serra, Giuseppe; A., Del Bimbo; L., Capodiferro. - STAMPA. - 6979:(2011), pp. 199-208. (Intervento presentato al convegno 16th International Conference on Image Analysis and Processing, ICIAP 2011 tenutosi a Ravenna, ita nel 2011-September) [10.1007/978-3-642-24088-1_21].

Space-time Zernike Moments and Pyramid Kernel Descriptors for Action Classification

SERRA, GIUSEPPE;
2011

Abstract

Action recognition in videos is a relevant and challenging task of automatic semantic video analysis. Most successful approaches exploit local space-time descriptors. These descriptors are usually carefully engineered in order to obtain feature invariance to photometric and geometric variations. The main drawback of space-time descriptors is high dimensionality and efficiency. In this paper we propose a novel descriptor based on 3D Zernike moments computed for space-time patches. Moments are by construction not redundant and therefore optimal for compactness. Given the hierarchical structure of our descriptor we propose a novel similarity procedure that exploits this structure comparing features as pyramids. The approach is tested on a public dataset and compared with state-of-the art descriptors.
2011
16th International Conference on Image Analysis and Processing, ICIAP 2011
Ravenna, ita
2011-September
6979
199
208
L., Costantini; L., Seidenari; Serra, Giuseppe; A., Del Bimbo; L., Capodiferro
Space-time Zernike Moments and Pyramid Kernel Descriptors for Action Classification / L., Costantini; L., Seidenari; Serra, Giuseppe; A., Del Bimbo; L., Capodiferro. - STAMPA. - 6979:(2011), pp. 199-208. (Intervento presentato al convegno 16th International Conference on Image Analysis and Processing, ICIAP 2011 tenutosi a Ravenna, ita nel 2011-September) [10.1007/978-3-642-24088-1_21].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11380/979940
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