Moving object detection apparatus and moving object detection method

A vector data classification apparatus which classifies vector data pieces into classes, each class including similar vector data pieces out of the vector data pieces, said vector data classification apparatus comprising:

• a vector data receiving unit configured to receive vector data pieces;
• a segmentation unit configured to perform segmentation so that the vector data pieces are divided into subsets each used for calculating a geodesic distance, and to set a part of the vector data pieces included in at least one of the subsets as a common point shared by the subsets;
• a distance calculation unit configured to calculate a distance representing a similarity between a pair of vector data pieces, for each of the subsets;
• a geodesic distance calculation unit configured to transform the distance calculated by said distance calculation unit into a geodesic distance which is a length of a path between the pair of vector data pieces via a vector data piece serving as a relay point;
• an approximate geodesic distance calculation unit configured to calculate an approximate geodesic distance bridging over the subsets, by integrating geodesic distances including the common points, among the geodesic distances obtained by said geodesic distance calculation unit;
• and
• a data classification unit configured to generate at least one class from the video sequence, by performing clustering using the calculated approximate geodesic distance so that similar vector data pieces are classified into one class.

A moving object detection method of detecting a moving object in a video sequence by extracting a region corresponding to a whole or a part of an image of the moving object, said moving object detection method comprising:

• receiving a set of images included in the video sequence;
• calculating movement trajectories, each of the movement trajectories being calculated by:
• detecting a motion of the image between a pair of images included in the set of images, for each pair of blocks included in the pair of images, each block having one or more pixels;
• and concatenating motions detected from all pairs of images included in the set of images;
• performing segmentation so that the movement trajectories are divided into subsets, and setting a part of the movement trajectories as common points shared by the subsets;
• calculating a distance representing a similarity between a pair of movement trajectories, for each of the subsets;
• transforming the calculated distance into a geodesic distance;
• calculating an approximate geodesic distance bridging over the subsets, by integrating geodesic distances including the common points, among the calculated geodesic distances;
• and
• extracting at least one region from the video sequence, by performing clustering using the calculated approximate geodesic distance so that blocks having similar movement trajectories are classified into one region.