• The Journal of the Korea Contents Association
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• v.10 no.4
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• pp.28-35
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• 2010

The variable block size motion estimation (ME) and compensation (MC) using multiple reference frames is adopted in H.264/AVC to improve coding efficiency. However, the computational complexity for ME/MC increases proportional to the number of reference frames and variable blocks. In this paper, we propose a new efficient reference frame selection algorithm to reduce the complexity while keeping the visual quality. First, a motion vector reference map is constructed by SAD of $4{\times}4$ block unit for multi reference frames. Next, the variable block size motion estimation and motion compensation is performed according to the motion vector reference map. The computer simulation results show that the average loss of BDPSNR is -0.01dB, the increment of BDBR is 0.27%, and the encoding time is reduced by 38% compared with the original method for H.264/AVC.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.10
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• pp.965-971
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• 2015

This paper suggests a feature point-based Iterative Closest Point (ICP) algorithm to compensate for the disparity error in building a two-dimensional map. The ICP algorithm is a typical algorithm for matching a common object in two different images. In the process of building a two-dimensional map using the laser scanner data, warping and distortions exist in the map because of the disparity between the two sensor values. The ICP algorithm has been utilized to reduce the disparity error in matching the scanned line data. For this matching process in the conventional ICP algorithm, pre-known reference data are required. Since the proposed algorithm extracts characteristic points from laser-scanned data, reference data are not required for the matching. The laser scanner starts from the right side of the mobile robot and ends at the left side, which causes disparity in the scanned line data. By finding the matching points between two consecutive frame images, the motion vector of the mobile robot can be obtained. Therefore, the disparity error can be minimized by compensating for the motion vector caused by the mobile robot motion. The validity of the proposed algorithm has been verified by comparing the proposed algorithm in terms of map-building accuracy to conventional ICP algorithm real experiments.