Parallel Contour Tracking for Mixed Reality Occlusion

The patent divides the image into multiple blocks and processes each block independently to obtain contour information. This segmentation allows parallel processing of different image regions while maintaining accurate contour detection in each block, thereby improving overall processing speed without sacrificing accuracy.

The patent introduces a block-based dimensional structure, organizing the image processing into a two-dimensional grid of blocks. This allows simultaneous processing across multiple blocks in parallel, transforming the traditional sequential one-dimensional processing approach into a parallel multi-dimensional approach that enhances processing efficiency.

By dividing the image into independent blocks, the patent enables parallel processing where each block can be processed separately using the same algorithm. This segmentation strategy allows efficient utilization of multiple calculation cores while keeping the processing logic within each block simple and uniform, thus managing complexity effectively.

The patent employs a universal processing algorithm that can be applied to any block in the image. This multi-functional approach allows the same processing logic to handle different blocks simultaneously, reducing the need for complex specialized processing routines and simplifying the overall system architecture while maintaining high processing efficiency.

The patent divides the image into multiple blocks and performs contour processing independently on each block. This segmentation eliminates the need for multiple iterative steps across the entire image, as each block can be processed in a single pass using parallel computation, thereby achieving both parallel processing capability and real-time performance.

The patent performs preliminary processing by dividing the image into blocks and preparing block-based data structures before contour extraction. This preliminary organization enables direct parallel processing of each block without requiring multiple iterative refinement steps, reducing overall processing time while maintaining parallel processing advantages.

By processing each block independently, the patent preserves the local contour characteristics of complex shapes within each block without applying global smoothing that would distort these features. This segmentation approach maintains accuracy of complex shapes while still providing sufficient smoothness for practical applications.

The patent applies contour processing locally to each block rather than globally across the entire image. This local quality approach allows each block to maintain its specific contour characteristics, including complex shapes, without being overly smoothed by global energy minimization, thereby preserving accuracy while achieving adequate smoothness.