Kyung-Hoon Bae

New disparity estimation scheme based on adaptive matching windows for intermediate view reconstruction

A new intermediate view reconstruction technique based on the adaptive disparity estimation algorithm is proposed. First, the feature values indicating the local image complexity are extracted from the input stereo image pair by using edge detection and matching algorithms. Then, the matching window size for disparity estimation is adaptively selected depending on the magnitude of these feature values. That is, for the region having larger feature values, the smaller matching window size is selected, while for the opposite case, the larger matching window size is selected by comparison with a predetermined threshold value. This new approach is not only able to reduce the mismatch of the disparity vector, which occurs in conventional fine disparity estimation with a small matching window size, but also can reduce the blocking effect, which occurs in coarse disparity estimation with a large matching window size. Some experimental results show that the proposed algorithm improves the peak signal-to-noise of the reconstructed intermediate view up to 2.93 to 4.09 dB and reduces the execution time to 39.34 to 65.62% on average in comparison with those of conventional algorithms.

A new stereo object tracking system using disparity motion vector

Abstract In this paper, a new stereo object tracking system using the disparity motion vector (DMV) is presented. In the proposed method, the time-sequential disparity maps are extracted from the sequence of the stereo input image pairs and then, the DMV defined as a disparity difference between two consecutive disparity maps is sequentially estimated from these disparity maps. Just like the motion vectors in the conventional video signals, the DMV provides us with motion information of a moving target by showing a relatively large change of the disparity values in the target areas. Accordingly, using this DMV the target area and its location coordinates can be detected. Basing on these locational data of a moving target, the pan/tilt embedded in the stereo camera system can be controlled and as a result, real-time stereo tracking of a moving target can be achieved. From some experiments with 9 frames of the stereo image pairs having 256xa0×xa0256 pixels, it is shown that the proposed DMV-based stereo object tracking system can track the moving target with a relatively low error ratio of about 3.05% on average.

Real-time stereo image watermarking using discrete cosine transform and adaptive disparity maps

In this paper, a real-time stereo image watermarking scheme using discrete cosine transform(DCT) and disparity map is proposed. That is, a watermark image is embedded into the right image of a stereo image pair in the frequency domain through the conventional DCT operation and disparity information between the watermarked right image and the left image is extracted. And then, the disparity data and the left image are simultaneously transmitted to the recipient through the communication channel. At the receiver, the watermarked right image is reconstructed from the received left image and disparity data through the adaptive matching algorithm and a watermark image is finally extracted from this reconstructed right image through the decoding algorithm. From some experiments by using the stereo image pair captured by the CCD camera and a watermark image of English alphabet NRL, it is found that the PSNR of the reconstructed right image through the DCT and adaptive matching algorithm improves to 9.3dB by comparing with those of the reconstructed right images through the conventional pixel-based and block-based matching algorithms. At the same time the PSNR of the watermark image extracted from the reconstructed right image also improve to 7.72dB by comparing with those of the others. These experimental results suggest a possibility of practical implementation of a disparity map-based stereo image watermarking scheme.

New watermark scheme for copyright protection of the stereovision system using adaptive disparity matching algorithm

In this paper, a new watermark scheme for copyright protection of the stereo vision system using adaptive disparity matching algorithm is proposed. That is, the right image of a stereo image is formulated to 8×8 blocks, in which each block is composed of 64×64 and the DCT coefficients for each of these blocks are computed and then, a specific watermark image having 64×64 pixels is embedded into these DCT coefficients. After disparity information is extracted from both of the watermarked right image and left image using a matching algorithm, the left image and disparity information is transmitted to the recipient through the communication channel. Then, the watermark is extracted from the reconstructed stereo image using the same seed value used in the embedding process. The watermark is extracted from the reconstructed right image as a result extraction performance of a watermark tightly depends on the employed disparity matching algorithms. From some experiments using a sequential stereo image of Fichier and the watermark image of English alphabet, it is shown that PSNR of the extracted watermark image from the reconstructed image by using an adaptive disparity matching algorithm improves to 3.68 dB on average by comparing with those of the pixel and block-matching algorithms.

Reconstruction of stereoscopic image using adaptive disparity estimation scheme

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 5.36~7.76 dB on the average than that of the conventional algorithms.

3D watermarking scheme in stereo vision system

In this paper, 3D watermarking scheme in stereo vision system is proposed. A watermark data is embedded into the right image of a stereo image pair by using the DWT algorithm and disparity data is extracted from the left and watermarked right images. And then, disparity data and the left image are transmitted to the recipient through the communication channel. At the receiver, the watermarked right image is reconstructed from the received left image and disparity data by employing the FMA. From the difference between the watermarked and original right images, the embedded watermark image can be finally extracted. From experiments using the stereo image pair of Friends and a watermark data of 3DRC, it is found that PSNR of the watermark image extracted from the reconstructed right image through the FMA and DWT algorithms can be increased up to 2.87dB, 2.58dB on average by comparing with those of the FMA and DCT algorithm when the quantizer Scale(Q.S) is kept to be 16 and 20, respectively.

Effective reconstruction of stereo images through regularized adaptive disparity estimation scheme

In this paper, an effective method of stereo image reconstruction through the regularized adaptive disparity estimation is proposed. Although the conventional adaptive disparity estimation method can sharply improve the PSNR of a reconstructed stereo image, but some problems of overlapping between the matching windows and disallocation of the matching windows can be occurred, because the matching window size changes adaptively in accordance with the magnitude of feature values. Accordingly, in this paper, a new regularized adaptive disparity estimation technique is proposed That is, by regularizing the estimated disparity vector with the neighboring disparity vectors, problems of the conventional adaptive disparity estimation scheme might be solved, and also the predicted stereo image can be more effectively reconstructed. From some experiments using the CCETTS stereo image pairs of Man and Claude, it is analyzed that the proposed disparity estimation scheme can improve PSNRs of the reconstructed images to 10.89dB, 6.13dB for Man and 1.41dB, 0.81dB for Claude by comparing with those of the conventional pixel-based and adaptive estimation method, respectively.

Adaptive disparity estimation scheme using balanced stereo image sequences

In this paper, an adaptive stereo matching method using a sequence of the balanced stereo image pair is proposed. The balanced stereo image pair can be acquired by applying the balance compensation scheme to the input stereo image pair, and then stereo matching is carried out by using the disparity vectors estimated from this balanced stereo image pair, in which the matching window size for disparity estimation is adaptively selected depending on the magnitude of the feature values. Because the balance compensation is able to alleviate the problem of luminance imbalance between the input stereo image pair, performance of the disparity estimation can be improved. Moreover, since the resultant image-smoothing effect occurring in the balanced stereo image can help to reduce not only the unreliable intensity matching but also the ambiguous matching in the process of disparity estimation, effective reconstruction of the stereo image can be expected as well. From some experiments using stereo image pairs of Piano and Claude, it is shown that the proposed method improves the PSNR of a reconstructed image up to 6.08 dB on average within the search ranges of ∮± 30 by comparing with that of conventional algorithms.

Web-based real-time multiview 3D display system

In this paper, a new web-based multi-view 3D display system through the intermediate views synthesis using an adaptive disparity estimation algorithm is proposed and its performance is analyzed by comparison to those of the conventional disparity estimation algorithms. First, the feature value indicating the local image complexity is extracted from the input stereo sequences by using the edge detection and disparity estimation. Then, the matching window size for disparity estimation is adaptively selected depending on the magnitude of this feature value. This new approach is not only able to reduce the disparity vector mismatch encountered in the conventional dense disparity estimation with small matching window size, but is also able to reduce the blocking effect associated with the disparity estimation using a large matching window size. With some experimental results on a sequence of stereo image captured by the web-cameras, it is found that the adaptive algorithm improves PSNRs on the average in comparison with those of the conventional algorithms and multi-view images can be generated through the process of real-time IVS. Finally it is suggested that this approach can be applied to the web-based real-time 3D video communication system.

Implementation of object-based multiview 3D display using adaptive disparity-based segmentation

In this paper, implementation of object-based multiview 3D display using object segmentation and adaptive disparity estimation is proposed and its performance is analyzed by comparison to that of the conventional disparity estimation algorithms. In the proposed algorithm, firstly we can get segmented objects by region growing from input stereoscopic image pair and then, in order to effectively synthesize the intermediate view the matching window size is selected according to the extracted feature value of the input stereo image pair. Also, the matching window size for the intermediate view reconstruction (IVR) is adaptively selected in accordance with the magnitude of the extracted feature value from the input stereo image pair. In addition, some experimental results on the IVR using the proposed algorithm is also discussed and compared with that of the conventional algorithms.