A Dynamic Programming Approach Based Stereo Vision Algorithm Improving Object Border Performance

The key issue of stereo vision algorithm using dynamic programming approach is to establish the cost function. Normally the cost of a match is the matching difference or matching error. This is almost the same for different algorithms in this approach. The only difference is in the cost of occlusion. Actually the cost of a known occluded point should be zero, because it is a good match. The difficulty is how to find the occluded region. In this paper, we present a new algorithm in which we first find the occluded region in the image using correlation approach. Then we establish a cost function in which the cost of the occluded region is set to zero. Then we use dynamic programming approach to minimize the energy of this cost function. Experimental results show that this algorithm can achieve excellent results with acceptable time efficiency

Authors

• Jun Zhao
• Jay Katupitiya

Keywords

• Dynamic programming
• Stereo vision
• Cost function
• Intelligent robots
• Manufacturing
• Australia
• Heuristic algorithms
• Robot vision systems
• Navigation
• Pixel
• Dynamic Approach
• Stereopsis
• Dynamic Programming Approach
• Object Borders
• South Wales State Government
• Correlation Approach
• Matching Error
• Occluded Regions
• Processing Time
• Image Pixels
• Line Scan
• Dynamic Algorithm
• White Areas
• Left Image
• Matching Strategy
• Correct Matches
• Left Border
• Plyometric
• Left View
• Nonzero Constant
• Sum Of Absolute Differences
• Previous Node
• Disparity Map
• Occlusion
• correlation