Design of Multi-Feature Parallel Tracking Algorithm for 3D Virtual Scene Images
3D virtual scene images have many features and are affected by factors such as changes in viewpoint and occlusion,which makes it difficult to extract image features.To address this problem,a multi-feature parallel tracking algorithm for 3D virtual scene images was proposed.Firstly,the algorithm calculated the image gradient to denoise the image,and then used the gray co-occurrence matrix to perform gray-level processing,thus calculating feature values.Moreover,a particle filter tracking algorithm was used to fuse multiple features.Meanwhile,a weighted fusion rule was introduced to determine the final position of each feature of the 3D virtual image,thus achieving multi-feature parallel tracking.Simulation results show that the proposed algorithm can accurately track multiple features of 3D virtual scene images with good robustness,and the tracking speed is only 23.4 frames per second.
3D virtual scene imageMultiple featuresParallel trackingGray co-occurrence matrix
万方数据
维普
