This paper presents a natural extension of the newly introduced "anti-face" method to event detection, both in the image and in the feature domains. In the case of the image domain (video sequences) we create spatio temporal templates by stacking the video frames, and the detection is performed on these templates. In order to recognize the motion of features in a video sequence, the spatial locations of the features are modulated in time, thus creating a one-dimensional vector which re resents the event The following applications of anti-sequences are presented 1) Detection of an object under 3D rotations in a video sequence simulated from the COIL database, 2) Visual speech recognition of spoken words, and 3) Recognition of symbols sketched with a laser pointer. The resulting detection algorithm is very fast, and is robust enough to work on small images. Also, it is capable of discriminating the desired event-template from arbitrary events, and not only events in a "negative training set".
['Margarita Osadchy', 'Daniel Keren', 'Yaniv Gal']
Anti-sequences: event detection by frame stacking