The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
배경이 복잡하고 부분적으로 가려진 상태에서 비디오에서 단단하지 않은 물체를 추적하는 것은 어렵습니다. 우리는 돌출 영역을 반복적으로 감지하고 연관시킴으로써 강성이 없는 객체 추적 패러다임을 제안합니다. 돌출 영역 분할은 각 프레임에서 작동됩니다. 분할 결과는 추적을 위한 풍부한 공간 지원을 제공하고 표류 없이 단단하지 않은 물체를 안정적으로 추적할 수 있도록 해줍니다. 두 명의 독립적인 관찰자를 사용하여 돌출 영역을 연관시킴으로써 정확한 객체 영역을 동시에 얻습니다. 우리의 공식은 매우 일반적이며 다른 주요 영역 분할 알고리즘도 사용할 수 있습니다. 실험 결과에 따르면 이러한 패러다임은 빠른 움직임, 회전 및 부분 폐색이 있는 객체의 추적 문제를 효과적으로 처리할 수 있는 것으로 나타났습니다.
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부
Xiaolin ZHAO, Xin YU, Liguo SUN, Kangqiao HU, Guijin WANG, Li ZHANG, "Non-rigid Object Tracking as Salient Region Segmentation and Association" in IEICE TRANSACTIONS on Information,
vol. E94-D, no. 4, pp. 934-937, April 2011, doi: 10.1587/transinf.E94.D.934.
Abstract: Tracking a non-rigid object in a video in the presence of background clutter and partial occlusion is challenging. We propose a non-rigid object-tracking paradigm by repeatedly detecting and associating saliency regions. Saliency region segmentation is operated in each frame. The segmentation results provide rich spatial support for tracking and make the reliable tracking of non-rigid object without drifting possible. The precise object region is obtained simultaneously by associating the saliency region using two independent observers. Our formulation is quite general and other salient-region segmentation algorithms also can be used. Experimental results have shown that such a paradigm can effectively handle tracking problems of objects with rapid movement, rotation and partial occlusion.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.E94.D.934/_p
부
@ARTICLE{e94-d_4_934,
author={Xiaolin ZHAO, Xin YU, Liguo SUN, Kangqiao HU, Guijin WANG, Li ZHANG, },
journal={IEICE TRANSACTIONS on Information},
title={Non-rigid Object Tracking as Salient Region Segmentation and Association},
year={2011},
volume={E94-D},
number={4},
pages={934-937},
abstract={Tracking a non-rigid object in a video in the presence of background clutter and partial occlusion is challenging. We propose a non-rigid object-tracking paradigm by repeatedly detecting and associating saliency regions. Saliency region segmentation is operated in each frame. The segmentation results provide rich spatial support for tracking and make the reliable tracking of non-rigid object without drifting possible. The precise object region is obtained simultaneously by associating the saliency region using two independent observers. Our formulation is quite general and other salient-region segmentation algorithms also can be used. Experimental results have shown that such a paradigm can effectively handle tracking problems of objects with rapid movement, rotation and partial occlusion.},
keywords={},
doi={10.1587/transinf.E94.D.934},
ISSN={1745-1361},
month={April},}
부
TY - JOUR
TI - Non-rigid Object Tracking as Salient Region Segmentation and Association
T2 - IEICE TRANSACTIONS on Information
SP - 934
EP - 937
AU - Xiaolin ZHAO
AU - Xin YU
AU - Liguo SUN
AU - Kangqiao HU
AU - Guijin WANG
AU - Li ZHANG
PY - 2011
DO - 10.1587/transinf.E94.D.934
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E94-D
IS - 4
JA - IEICE TRANSACTIONS on Information
Y1 - April 2011
AB - Tracking a non-rigid object in a video in the presence of background clutter and partial occlusion is challenging. We propose a non-rigid object-tracking paradigm by repeatedly detecting and associating saliency regions. Saliency region segmentation is operated in each frame. The segmentation results provide rich spatial support for tracking and make the reliable tracking of non-rigid object without drifting possible. The precise object region is obtained simultaneously by associating the saliency region using two independent observers. Our formulation is quite general and other salient-region segmentation algorithms also can be used. Experimental results have shown that such a paradigm can effectively handle tracking problems of objects with rapid movement, rotation and partial occlusion.
ER -