{"id":10923,"date":"2026-08-26T20:10:54","date_gmt":"2026-08-26T12:10:54","guid":{"rendered":"\/jase\/?post_type=tkuisotope&p=10923"},"modified":"2026-08-29T18:16:19","modified_gmt":"2026-08-29T10:16:19","slug":"a-novel-stereo-object-segmentation-algorithm-using-disparity-and-temporal-information","status":"publish","type":"tkuisotope","link":"\/jase\/?tkuisotope=a-novel-stereo-object-segmentation-algorithm-using-disparity-and-temporal-information","title":{"rendered":"A Novel Stereo Object Segmentation Algorithm Using Disparity and Temporal Information"},"content":{"rendered":"\n
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<\/i> 2013<\/a><\/p>\n<\/div>\n\n\n\n

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<\/i> Volume 16, Issue 3<\/a><\/p>\n<\/div>\n\n\n\n

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Jing Chen1,2<\/sup><\/i><\/a>, Can-Hui Cai2<\/sup>, Cui-Hua Li1<\/sup><\/p>\n\n\n\n

1<\/sup>School of Information Science and Engineering, Xiamen University<\/p>\n\n\n\n

2<\/sup>Institute of Information Science and Engineering, Huaqiao University<\/p>\n<\/div>\n\n\n\n

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Received: February 27, 2013
Accepted: June 28, 2013
Publication Date: September 1, 2013<\/p>\n<\/div>\n<\/div>\n\n\n\n

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The diagram of the proposed algorithm.<\/p>\n<\/div>\n<\/div>\n\n\n\n

<\/i> Copyright <\/strong>The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0)<\/a>, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are cited.<\/p>\n\n\n\n

Download Citation:  BibTeX <\/a>| http:\/\/dx.doi.org\/10.6180\/jase.2013.16.3.01<\/a>  <\/p>\n\n\n\n

Download PDF<\/a><\/p>\n\n\n\n

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A novel stereoscopic object segmentation method based on disparity and temporal-spatial cues is proposed in this paper. First, a foreground layer map is generated from a patched disparity image and a motion object map is produced using an adaptive reference frame selection method. Then the intersection of these two maps is used to extract the foreground motion objects. In the foreground layer map generation stage, two intensity image sequences of the input stereo videos are separately mapped to the rank space by a rank transform to eliminate the parameter deviation of binocular cameras, and reduce the interference of the environment fluctuation and noises. A fast multi-window matching strategy is proposed to speed up the stereo matching process. Then, a disparity patching process is performed to bridge the disparity discontinuity in the smooth region to improve the accuracy of the disparity map. In the motion object map generation stage, an adaptive reference frame selection method is introduced to obtain salient motion and produce the motion mask of each view. Experimental results have indicated the good performance and the practicability of the proposed stereo segmentation algorithm.<\/p>\n\n\n\n

Keywords: Disparity Estimation; Stereo Matching; Rank Transform; Disparity Map<\/em><\/p>\n\n\n\n

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  1. [1] Zhang, Q. and Ngan, K. N., “Segmentation and Tracking Multiple Objects under Occlusion from Multiview Video,” IEEE Transactions on Image Processing, Vol. 20, No. 11, pp. 3308-3313 (2011). doi: 10.1109\/TIP.2011.2159228<\/li>\n
  2. [2] Tola, E., Lepetit, V. and Daisy, F. P., “An Efficient Dense Descriptor Applied to Wide-Baseline Stereo,” IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 32, pp. 815-830 (2010). doi: 10.1109\/TPAMI.2009.77<\/li>\n
  3. [3] Kanade, T. and Okutomi, M., “A Stereo Matching Algorithm with an Adaptive Window: Theory and Experiment,” IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 16, pp. 920-932 (1994). doi: 10.1109\/34.310690<\/li>\n
  4. [4] Tang, L., Wu, C. and Chen, Z., “Image Dense Matching Based on Region Growth with Adaptive Window,” Pattern Recognition Letters, Vol. 23, pp. 1169-1178 (2002). doi: 10.1016\/S0167-8655(02)00063-6<\/li>\n
  5. [5] Yoon, K. and Kweon, I., “Adaptive Support-Weight Approach for Correspondence Search,” IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 24, pp. 650-656 (2006). doi: 10.1109\/TPAMI.2006.70<\/li>\n
  6. [6] Banks, J. and Bennamoun, M., “Reliability Analysis of the Rank Transform for Stereo Matching,” IEEE Transactions on Systems Man and Cybernetics, Part B, Vol. 31, Issue 6, pp. 870-880 (2001). doi: 10.1109\/3477.969491<\/li>\n
  7. [7] Kolmogorov, V., Criminisi, A., Blake, A., Cross, G. and Rother, C., “Probabilistic Fusion of Stereo with Color and Contrast for Bilayer Segmentaion,” IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 28, pp. 1480-1492 (2006). doi: 10.1109\/TPAMI.2006.193<\/li>\n
  8. [8] Wu, Y., Wang, P. P. and Li, J., “Bi-Layer Segmentation from Stereo Video Sequences by Fusing Multiple Cues,” IEEE Int. Conf. on Multimedia and Expo (ICME), Vol. 1, pp. 1353-1356 (2008). doi: 10.1109\/ICME.2008.4607694<\/li>\n
  9. [9] Chen, Y. and Cai, C., “Two-Level Stereo Matching Based on Rank Transform Domain,” Computer Engineering and Applications, Vol. 44, No. 34, pp. 188-190 (2008).<\/li>\n
  10. [10] Middlebury. http:\/\/vision.middlebury.edu\/stereo.<\/li>\n
  11. [11] Fusiello, A., Roberto, V. and Trucco, E., “Efficient Stereo with Multiple Windowing,” IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 858-863 (1997). doi: 10.1109\/CVPR.1997.609428<\/li>\n
  12. [12] Karsten, Dennis, M., Hesser, D. and Reinhard, J., “Calculating Dense Disparity Maps from Color Stereo Images, an Efficient Implementation,” IEEE Workshop on Stereo and Multi-Baseline Vision, pp. 30-36 (2001). doi: 10.1109\/SMBV.2001.988760<\/li>\n
  13. [13] i2idatabase. http:\/\/research.microsoft.com\/en-us\/projects\/i2i\/data.aspx.<\/li>\n<\/ol>\n<\/div>\n\n\n\n

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