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1. (US20090207313) Distributing candidate vectors based on local motion complexity
Note: Texte fondé sur des processus automatiques de reconnaissance optique de caractères. Seule la version PDF a une valeur juridique

Claims

1. A method for distributing candidate motion vectors, the method comprising:
dividing a picture frame into a plurality of segments using a processor, each segment comprising a plurality of pixel blocks;
measuring local motion complexity for each segment using the processor; and
assigning a number of candidate motion vectors to pixel blocks within each segment based on the measured local motion complexity using the processor, wherein the number of candidate motion vectors assigned to pixel blocks within one of the segments is different from the number of candidate motion vectors assigned to pixels blocks within another one of the segments,
wherein the measuring local motion complexity further comprises:
determining a sum-of-absolute differences between pixel blocks of the picture frame and corresponding pixel blocks of an adjacent frame; and
summing the measured sum-of-absolute differences associated with of pixel blocks within each segment,
wherein the assigning further comprises using a distribution function configured to assign the number of candidate vectors based on the measured local motion complexity of each segment, and
wherein the distribution function is based on a maximum, minimum or average of the measured sum-of-absolute differences (SAD) of the segments using the following respective relationships:

           N_max= a +b*SAD_max + c*SAD_max*SAD 13max,

           N_min= a +b*SAD_min + c*SAD_min*SAD_min, and

           N_av= a +b* SAD_av + c*SAD_av*SAD_av.
2. The method of claim 1, wherein the distribution function is further based on predetermined values for a maximum, minimum or average number of candidate vectors per block.
3. The method of claim 1, further comprising performing motion estimation on the pixel blocks using the number of candidate vectors assigned to each pixel block.
4. A system for distributing candidate vectors, the system comprising a processor configured for:
dividing a picture frame into a plurality of segments, each segment comprising a plurality of pixel blocks;
measuring local motion complexity for each segment; and
assigning a number of candidate motion vectors to pixel blocks within each segment based on the measured local motion complexity, wherein the number of candidate motion vectors assigned to pixel blocks within one of the segments is different from the number of candidate motion vectors assigned to pixels blocks within another one of the segments,
wherein the measuring local motion complexity comprises:
determining a sum-of-absolute differences between pixel blocks of the picture frame and corresponding pixel blocks of an adjacent frame; and
summing the measured sum-of-absolute differences associated with of pixel blocks within each segment,
wherein assigning comprises using a distribution function configured to assign the number of candidate vectors based on the measured local motion complexity of each segment, and
wherein the distribution function is based on a maximum, minimum or average of the measured sum-of-absolute differences (SAD) of the segments using the following respective relationships:

           N_max= a +b*SAD_max + c*SAD_max*SAD_max,

           N_min= a +b*SAD_min + c*SAD_min*SAD_min, and

           N_av= a +b* SAD_av + c*SAD_av*SAD_av.
5. The system of claim 4, wherein the distribution function is further based on predetermined values for a maximum, minimum, or average number of candidate vectors per block.
6. The system of claim 4, wherein the processor is further configured for performing motion estimation on the pixel blocks using the number of candidate vectors assigned to each pixel block.