iCoseg: Interactive Co-segmentation with Intelligent Scribble Guidance

被引:323
作者
Batra, Dhruv [1 ]
Kowdle, Adarsh [2 ]
Parikh, Devi [3 ]
Luo, Jiebo [4 ]
Chen, Tsuhan [2 ]
机构
[1] Carnegie Mellon Univ, Pittsburgh, PA 15213 USA
[2] Cornell Univ, Ithaca, NY 14853 USA
[3] TTIC, Chicago, IL USA
[4] Eastman Kodak Co, Rochester, NY 14650 USA
来源
2010 IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR) | 2010年
关键词
D O I
10.1109/CVPR.2010.5540080
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper presents an algorithm for Interactive Co-segmentation of a foreground object from a group of related images. While previous approaches focus on unsupervised co-segmentation, we use successful ideas from the interactive object-cutout literature. We develop an algorithm that allows users to decide what foreground is, and then guide the output of the co-segmentation algorithm towards it via scribbles. Interestingly, keeping a user in the loop leads to simpler and highly parallelizable energy functions, allowing us to work with significantly more images per group. However, unlike the interactive single image counterpart, a user cannot be expected to exhaustively examine all cutouts (from tens of images) returned by the system to make corrections. Hence, we propose iCoseg, an automatic recommendation system that intelligently recommends where the user should scribble next. We introduce and make publicly available the largest co-segmentation dataset yet, the CMU-Cornell iCoseg Dataset, with 3 8 groups, 6 4 3 images, and pixelwise hand-annotated groundtruth. Through machine experiments and real user studies with our developed interface, we show that iCoseg can intelligently recommend regions to scribble on, and users following these recommendations can achieve good quality cutouts with significantly lower time and effort than exhaustively examining all cutouts.
引用
收藏
页码:3169 / 3176
页数:8
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