吉林大学学报(工学版) ›› 2013, Vol. 43 ›› Issue (04): 1116-1120.doi: 10.7964/jdxbgxb201304043

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Algorithm for optimal homography matrix in video mosaic

ZHANG Chun-yu1, WANG Wen1, QIU Ya-te1, GUO Ke-you2   

  1. 1. Research Institute of Highway, Ministry of Transportation, Beijing Chengda Traffic Technology Co.Ltd,Beijing 100088,China;
    2. College of Mechanical Engineering and Automation,Beijing Technology and Business University, Beijing 100037,China
  • Received:2012-12-22 Online:2013-07-01 Published:2013-07-01

Abstract:

We propose an algorithm for optimal homography matrix in video mosaic using double thread. First, the characteristic points are extracted using Speeded Up Robust Feature (SURF) method. Second, the corresponding characteristic points are matched using Nearest Neighbor (NN) and Random Sample Consensus (RANSAC) methods. Third, the optimal homography matrix of first k video frames is calculated using the normal covariance correlation of overlapped area between corresponding frames. The optimal homography matrix is taken as the mapping matrix of the succeeding frames. Meanwhile, the KLT algorithm is used for feature dynamic tracking of the frames succeeding k+1 frame. If the change of amount of the tracked feature points exceeds the given threshold, the current optimal homgoraphy matrix needs re-optimization and transformation; the pairs of feature points of k video frames are recalculated and matched to obtain the new optimal homgoraphy matrix. Image matching tests in traffic surveillance demonstrate that the average matching speed of the proposed algorithm is less than 100 ms; good matching quality is achieved for images with variable rotation, scaling, visual angle and illumination; parameter estimation is accurate and high speed with less computation, which meets the requirements of real-time and high accurate matching of the system.

Key words: information processing, video image mosaic system, speeded up robust features(SURF), optimal homography matrix

CLC Number: 

  • TN911

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