In this paper, a new stereoscopic image reconstruction technique using an adaptive disparity estimation algorithm is proposed and its performance is analyzed in terms of PSNR through comparison to that of the conventional disparity estimation algorithms. In the proposed method, the feature-based disparity estimation method in which Canny mask operator is used for detecting the edge information from the input stereo pair are used for extracting the feature value. And, the matching window size for reconstruction of stereoscopic image is adaptively selected depending on the magnitude of the feature value of the input stereo pair by comparing with the predetermined threshold value. That is, coarse matching is carried out in the region having a small feature value while dense matching is carried out in the region having a large feature value. This new approach can not only reduce mismatching possibility of the disparity vector mostly happened in the conventional dense disparity estimation with a small matching window size, but also reduce the blocking effect occurred in the disparity estimation with a large matching window size. From some experimental results, it is found that the proposed algorithm improves PSNR of the reconstructed image about 5.367.76 dB on the average than that of the conventional algorithms.

In this paper, a new 3D intermediate views reconstruction technique using an adaptive disparity estimation algorithm is proposed and its performance is analyzed by comparison to that of the conventional disparity estimation algorithms. In the proposed algorithm, in order to effectively synthesize the intermediate views the matching window size is selected according to the feature value of the input stereo image. By doing this, the mismatching probability of the disparity can be reduced through coarse matching in the similar area and fine matching in the area having large feature values such as in the edge part of object. From some experimental results, it is found that the proposed algorithm improves the PSNR of the reconstructed intermediate views about 3-4 dB on the average than that of the conventional algorithms.

In this paper, a new effective 3D object remote-tracking system using the disparity information is suggested, in which not only the target object can be tracked in real-time, but also the target object is displayed in 3D at the receiver by only using the disparity information taken from the stereo object images. By using the disparity information of stereo image sequences, the target object can be detected and its location coordinates are extracted and then, using these coordinate values the stereo object tracking is accomplished by controlling the stereo camera that is mounted on a pan/tilt. And, the disparity information is sent to the receiver together with the reference image for effective 3D reconstruction of the target image under tracking. Some experimental results show the proposed system has much less transmitting data and shorter processing time for real-time 3D target tracking through the comparison to those of the conventional algorithms.

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