An active area of anomalous and suspicious behavior detection from patterns is based on visual modalities, such as a camera. Zhang, et al. (2007) proposed a system for a visual human motion analysis from a video sequence, which recognizes unusual behavior based on walking trajectories; Lin, et al. (2009) described a video surveillance system based on color features, distance features, and a count feature, where evolutionary techniques are used to measure observation similarity. The system tracks each person and classifies their behavior by analyzing their trajectory patterns. The system extracts a set of visual low-level features in different parts of the image, and performs a classification with SVMs in order to detect aggressive, cheerful, intoxicated, nervous, neutral, and tired behavior.