The architecture shown can perform global search, local search and local sub pixel search in a parallel or in a pipelined mode. All operations are in a streaming mode without the requirement of external intermediate data storage.

The invention has an object to reduce computing costs in object identification in a video to below conventional levels. A signal processing unit for processing a video composed of a plurality of frames includes: an object identification unit configured to identify an object represented in the video; and a window specification unit configured to specify, based on a position in an (N+1)-th frame of the video of a representation of the object that appears in an N-th frame, an identification target region to be subjected to object identification in the (N+1)-th frame by the object identification unit, where N is a natural number.

A system and method include acquisition of a plurality of projection images of a subject, each of the projection images associated with a respective projection angle, determination, for each of the projection images, of a center-of-light location in a first image region, determination of a local fluctuation measure based on the determined center-of-light locations, and determination of a quality measure associated with the plurality of projection images based on the local fluctuation measure.

An object detection and tracking method and system are provided. The object detection and tracking method includes the following steps: (i) selecting one of a plurality of frames of a video as a current frame, (ii) searching in an object tracker searching area of the current frame to generate a current object tracker, (iii) searching in each auxiliary tracker searching area of the current frame to individually generate a current auxiliary tracker, (iv) when the current object tracker is located at a block different from the blocks located by the generated object trackers, generating a new auxiliary tracker at the central position of the current frame, and (v) repeating the above steps until all the frames have been processed.

An object detection and tracking method and system are provided. The object detection and tracking method includes the following steps: (i) selecting one of a plurality of frames of a video as a current frame, (ii) searching in an object tracker searching area of the current frame to generate a current object tracker, (iii) searching in each auxiliary tracker searching area of the current frame to individually generate a current auxiliary tracker, (iv) when the current object tracker is located at a block different from the blocks located by the generated object trackers, generating a new auxiliary tracker at the central position of the current frame, and (v) repeating the above steps until all the frames have been processed.

The architecture shown can perform global search, local search and local sub pixel search in a parallel or in a pipelined mode. All operations are in a streaming mode without the requirement of external intermediate data storage.

The architecture shown can perform global search, local search and local sub pixel search in a parallel or in a pipelined mode. All operations are in a streaming mode without the requirement of external intermediate data storage.

An imaging method with motion detection includes determining a windows layout according to a vanishing point or a horizontal line, sizes of windows in the determined windows layout being not uniform; determining features of the windows of a current image; comparing the determined features of the windows of the current image with features of corresponding windows of a previous image to determine whether local motion occurs.

A motion estimation method for video data including frames and an apparatus therefor are provided. The motion estimation method includes determining whether a current frame unit for which motion estimation is to be performed corresponds to a double block, when the current frame unit corresponds to a double block, acquiring a candidate vector set corresponding to a first single block included in the double block, as a candidate vector set of the double block, individually calculating a confidence function value of each candidate vector included in the candidate vector set of the double block, for the first single block and a second single block included in the double block, and acquiring an estimated motion vector of the first single block and an estimated motion vector of the second single block, based on the calculated confidence function value of each candidate vector.

A motion estimation method for video data including frames and an apparatus therefor are provided. The motion estimation method includes determining whether a current frame unit for which motion estimation is to be performed corresponds to a double block, when the current frame unit corresponds to a double block, acquiring a candidate vector set corresponding to a first single block included in the double block, as a candidate vector set of the double block, individually calculating a confidence function value of each candidate vector included in the candidate vector set of the double block, for the first single block and a second single block included in the double block, and acquiring an estimated motion vector of the first single block and an estimated motion vector of the second single block, based on the calculated confidence function value of each candidate vector.