Abstract: A crowd motion summarization method that provides a rich, real-time description of the crowd's characteristics from a video, such as, speed, orientation, count, spatial locations, and time. A feature tracking module receives each video frame and detects features (feature points) from the video frame. A crowd occupancy detection module receives the video frame and generates a binary crowd occupancy map having human pixel positions which indicate the human location versus non-human location, and generates a total human count of humans detected in the video frame. The feature tracking module generates feature tracking information for only those features contained in the human pixel positions which indicate the human location. In an example, the detected features are Kanade-Lucas-Tomasi (KLT) features. A feature-crowd matching module generates, using the feature tracking information and the total human count: crowd motion data. The method outputs the crowd motion data.

Abstract: A crowd motion summarization method that provides a rich, real-time description of the crowd's characteristics from a video, such as, speed, orientation, count, spatial locations, and time. A feature tracking module receives each video frame and detects features (feature points) from the video frame. A crowd occupancy detection module receives the video frame and generates a binary crowd occupancy map having human pixel positions which indicate the human location versus non-human location, and generates a total human count of humans detected in the video frame. The feature tracking module generates feature tracking information for only those features contained in the human pixel positions which indicate the human location. In an example, the detected features are Kanade-Lucas-Tomasi (KLT) features. A feature-crowd matching module generates, using the feature tracking information and the total human count: crowd motion data. The method outputs the crowd motion data.