Generating a Motion Attention Model

• US 20060165178A1
• Filed: 04/03/2006
• Published: 07/27/2006
• Est. Priority Date: 11/01/2002
• Status: Active Grant

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Corporation
• Inventors: Zhang, Hong-Jiang, Ma, Yu-Fei
• Granted Patent: US 8,098,730 B2
• Time in Patent Office: Days
• US Class Current: 375/240.160
• CPC Class Codes: G06T 7/215 Motion-based segmentation
• CPC Class Codes: G06V 10/462 Salient features, e.g. scale invariant feature transforms [SIFT]
• CPC Class Codes: G06V 20/40 in video content extracting overlay text G06V20/62; video retrieval G06F16/70; processing of video elementary streams in video servers H04N21/234; processing of video elementary streams in video clients H04N21/44

Abstract

Systems and methods to generate a motion attention model of a video data sequence are described. In one aspect, a motion saliency map B is generated to precisely indicate motion attention areas for each frame in the video data sequence. The motion saliency maps are each based on intensity I, spatial coherence Cs, and temporal coherence Ct values. These values are extracted from each block or pixel in motion fields that are extracted from the video data sequence. Brightness values of detected motion attention areas in each frame are accumulated to generate, with respect to time, the motion attention model.

Claims

1. A method for generating a motion attention model of a video data sequence, the method comprising:

generating a motion saliency map B to precisely indicate motion attention areas for each frame in the video data sequence, the motion saliency map being based on intensity I, spatial coherence Cs, and temporal coherence Ct values from each location of a block MBij in motion fields extracted from the video data sequence; and

accumulating brightness of detected motion attention areas to generate, with respect to time, a motion attention model for the video data sequence.

2. The method of claim 1, wherein the video data sequence is in an MPEG data format.

3. The method of claim 1, wherein the motion field is a motion vector field or an optical flow field.

4. A computer-readable medium for generating a motion attention model of a video data sequence, the computer-readable medium comprising computer-program instructions executable by a processor for:

generating a motion saliency map B to precisely indicate motion attention areas for each frame in the video data sequence, the motion saliency map being based on intensity I, spatial coherence Cs, and temporal coherence Ct values from each location of a block MBij in motion fields extracted from the video data sequence; and

accumulating brightness of detected motion attention areas to generate, with respect to time, a motion attention model for the video data sequence.

5. A computing device for generating a motion attention model of a video data sequence, the computing device comprising:

means for generating a motion saliency map B to precisely indicate motion attention areas for each frame in the video data sequence, the motion saliency map being based on intensity I, spatial coherence Cs, and temporal coherence Ct values from each location of a block MBij in motion fields extracted from the video data sequence; and

means for accumulating brightness of detected motion attention areas to generate, with respect to time, a motion attention model for the video data sequence.