Correction: novel Kernel-based recognizers of human actions

The approach is taken further by Schindler and Van Gool [24], who investigated the detection of actions from very short sequences called snippets. Two separate pathways for motion and shape are considered. Motion is modeled by means of optical flow, computed for different directions and scales. Shape is represented by Gabor filter responses. MAX-pooling and comparison with a set of templates (learned using PCA) yield high-level feature vectors, which are classified through SVMs. In our approach, we feed our classification algorithm by such a powerful feature descriptor, independently computed for each pair of frames.