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ICIAP
2009
ACM

Video Event Classification Using Bag of Words and String Kernels

8 years 2 months ago
Video Event Classification Using Bag of Words and String Kernels
Abstract. The recognition of events in videos is a relevant and challenging task of automatic semantic video analysis. At present one of the most successful frameworks, used for object recognition tasks, is the bag-ofwords (BoW) approach. However this approach does not model the temporal information of the video stream. In this paper we present a method to introduce temporal information within the BoW approach. Events are modeled as a sequence composed of histograms of visual features, computed from each frame using the traditional BoW model. The sequences are treated as strings where each histogram is considered as a character. Event classification of these sequences of variable size, depending on the length of the video clip, are performed using SVM classifiers with a string kernel that uses the Needlemann-Wunsch edit distance. Experimental results, performed on two datasets, soccer video and TRECVID 2005, demonstrate the validity of the proposed approach. Key words: video annotation...
Lamberto Ballan, Marco Bertini, Alberto Del Bimbo,
Added 19 Feb 2011
Updated 24 Jun 2013
Type Journal
Year 2009
Where ICIAP
Authors Lamberto Ballan, Marco Bertini, Alberto Del Bimbo, Giuseppe Serra
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