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Audio-visual event classification via spatial-temporal ...
https://ieeexplore.ieee.org/document/4761474/#:~:text=Audio-visual%20event%20classification%20via%20spatial-temporal-audio%20words%20Abstract%3AIn%20this,an%20extended%20probabilistic%20latent%20semantic%20analysis%20%28pLSA%29%20model.
Audio-Visual Event Classification via Spatial-Temporal ...
https://www.cs.uml.edu/~ycao/research/ICPR_08_Camera_Ready.pdf
approach for audio-visual event classification. This approach is based on a new unsupervised learning method using an extended probabilistic Latent Semantic Analysis (pLSA) model. We represent each video clip as a collection of spatial-temporal-audio words, which are generated by fusing the visual and audio features using the pLSA model. Each audio-
Audio-visual event classification via spatial-temporal ...
https://ieeexplore.ieee.org/document/4761474/
Audio-visual event classification via spatial-temporal-audio words Abstract: In this paper, we propose a generative model-based approach for audio-visual event classification. This approach is based on a new unsupervised learning method using an extended probabilistic latent semantic analysis (pLSA) model.
Audio-Visual Event Classification via Spatial-Temporal ...
https://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.485.4734
Each audio-visual event class is treated as the latent topic in this model. The probability distributions of the spatial-temporal-audio words are learned from training examples, which include a sequence of videos that represent different types of audio-visual events. Experimental results show the effectiveness of the proposed approach. Keyphrases
Audio-Visual Event Classification via Spatial-Temporal ...
https://www.researchgate.net/publication/224375241_Audio-Visual_Event_Classification_via_Spatial-Temporal-Audio_Words
Two of our current focuses are: medical video event classification using shared features [12] and audio-visual event classification via spatial-temporal-audio words [13]. The first service ...
Audio-Visual Event Classification via Spatial-Temporal ...
https://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.214.5113
Each audiovisual event class is treated as the latent topic in this model. The probability distributions of the spatialtemporal-audio words are learnt from training examples, which include a sequence of videos that represent different types of audio-visual events. Experimental results show the effectiveness of the proposed approach. 1. Keyphrases
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