Comments Off on Video Event Classification using String Kernels

By lambertoballan, September 22, 2009

Our paper on “Video Event Classification using String Kernels“ was accepted for publication by Springer International Journal on Multimedia Tools and Applications (MTAP) in the special issue on Content-Based Multimedia Indexing.

In this paper we present a method to introduce temporal information for video event recognition within the bag-of-words (BoW) approach. Events are modeled as a sequence composed of histograms of visual features, computed from each frame using the traditional BoW. The sequences are treated as strings phrases where each histogram is considered as a character. Event classification of these sequences of variable length, depending on the duration of the video clips, are performed using SVM classifiers with a string kernel that uses the Needlemann-Wunsch edit distance.