Please use this identifier to cite or link to this item: http://localhost/handle/Hannan/122389
Title: Interactive Video Segmentation via Local Appearance Model
Authors: Chong Sun;Huchuan Lu
Year: 2017
Publisher: IEEE
Abstract: In numerous video segmentation algorithms, shape and color priors from previous frames are propagated to successive frames for processing. One prime issue of the existing algorithms is how priors are modeled and propagated effectively. This paper proposes a novel algorithm for accurate and robust foreground prediction via a local appearance model based on shape and color. In the shape estimation process, instead of performing global matching, a local search mechanism is developed to capture complex motions. In addition, global information is used to facilitate local matching for the final shape estimation. Color cues from multiple frames are used to estimate the foreground (background) pixel distribution in the current image. Furthermore, the contribution of each frame is weighted based on its reliability and discriminative strength. Based on the proposed local appearance model, a graph cut algorithm is used to generate segmentation results. The experimental results show that accurate video segmentation can be obtained by the proposed algorithm with fewer user interactions.
URI: http://localhost/handle/Hannan/122389
volume: 27
issue: 7
More Information: 1491,
1501
Appears in Collections:2017

Files in This Item:
File SizeFormat 
7434622.pdf3.6 MBAdobe PDF
Title: Interactive Video Segmentation via Local Appearance Model
Authors: Chong Sun;Huchuan Lu
Year: 2017
Publisher: IEEE
Abstract: In numerous video segmentation algorithms, shape and color priors from previous frames are propagated to successive frames for processing. One prime issue of the existing algorithms is how priors are modeled and propagated effectively. This paper proposes a novel algorithm for accurate and robust foreground prediction via a local appearance model based on shape and color. In the shape estimation process, instead of performing global matching, a local search mechanism is developed to capture complex motions. In addition, global information is used to facilitate local matching for the final shape estimation. Color cues from multiple frames are used to estimate the foreground (background) pixel distribution in the current image. Furthermore, the contribution of each frame is weighted based on its reliability and discriminative strength. Based on the proposed local appearance model, a graph cut algorithm is used to generate segmentation results. The experimental results show that accurate video segmentation can be obtained by the proposed algorithm with fewer user interactions.
URI: http://localhost/handle/Hannan/122389
volume: 27
issue: 7
More Information: 1491,
1501
Appears in Collections:2017

Files in This Item:
File SizeFormat 
7434622.pdf3.6 MBAdobe PDF
Title: Interactive Video Segmentation via Local Appearance Model
Authors: Chong Sun;Huchuan Lu
Year: 2017
Publisher: IEEE
Abstract: In numerous video segmentation algorithms, shape and color priors from previous frames are propagated to successive frames for processing. One prime issue of the existing algorithms is how priors are modeled and propagated effectively. This paper proposes a novel algorithm for accurate and robust foreground prediction via a local appearance model based on shape and color. In the shape estimation process, instead of performing global matching, a local search mechanism is developed to capture complex motions. In addition, global information is used to facilitate local matching for the final shape estimation. Color cues from multiple frames are used to estimate the foreground (background) pixel distribution in the current image. Furthermore, the contribution of each frame is weighted based on its reliability and discriminative strength. Based on the proposed local appearance model, a graph cut algorithm is used to generate segmentation results. The experimental results show that accurate video segmentation can be obtained by the proposed algorithm with fewer user interactions.
URI: http://localhost/handle/Hannan/122389
volume: 27
issue: 7
More Information: 1491,
1501
Appears in Collections:2017

Files in This Item:
File SizeFormat 
7434622.pdf3.6 MBAdobe PDF