Several types of features, such as Hue-Saturation, Color moments, number of faces detected, and sparse local interest points, were extracted at all frames of videos and discretized using k-means vector quantization and accumulated into histograms. All histograms are concatenated into a 25,000 dimensional video-level feature vector, connectd with multilayer neural network with Relu followed by a Softmax classifier.