Normalized Cuts and Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Learning a Classification Model for Segmentation
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
"GrabCut": interactive foreground extraction using iterated graph cuts
ACM SIGGRAPH 2004 Papers
Pictorial Structures for Object Recognition
International Journal of Computer Vision
Histograms of Oriented Gradients for Human Detection
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Closely Coupled Object Detection and Segmentation
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01
Shape Guided Object Segmentation
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
Random Walks for Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
The Representation and Matching of Pictorial Structures
IEEE Transactions on Computers
Inferring semantic concepts from community-contributed images and noisy tags
MM '09 Proceedings of the 17th ACM international conference on Multimedia
TurboPixels: Fast Superpixels Using Geometric Flows
IEEE Transactions on Pattern Analysis and Machine Intelligence
OBJCUT: Efficient Segmentation Using Top-Down and Bottom-Up Cues
IEEE Transactions on Pattern Analysis and Machine Intelligence
Object Detection with Discriminatively Trained Part-Based Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
Automatic body segmentation with graph cut and self-adaptive initialization level set (SAILS)
Journal of Visual Communication and Image Representation
Performance evaluation of image segmentation
ICIAR'06 Proceedings of the Third international conference on Image Analysis and Recognition - Volume Part I
Articulated pose estimation with flexible mixtures-of-parts
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
Learning effective human pose estimation from inaccurate annotation
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
Arbitrary body segmentation in static images
Pattern Recognition
Segmentation of objects in a detection window by Nonparametric Inhomogeneous CRFs
Computer Vision and Image Understanding
Intelligent Multimedia Analysis for Security Applications
Intelligent Multimedia Analysis for Security Applications
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Human body segmentation in images is desirable in various practical applications, e.g., content-based image retrieval. However, it remains a challenging problem due to various body poses and confusing background. To overcome these difficulties, two properties of human body are explored in this paper, i.e., complementary property and weak structure property. Complementary property means that different human body parts always have the similar appearances. With this property, we propose to construct the Part Appearance Map (PAM). PAM can effectively represent the appearance probability of what a pixel belong to a human body, even for inaccurate human pose obtained by pictorial structure model. Afterward, robust foreground and background seeds are acquired by PAM. To utilize the structure information of human body effectively, we propose a novel graph cuts method - spatial constraint based graph cuts (SCGC), which incorporates weak structure property of human body parts into the cost function. The weak structure property constrains the arms, legs and head to appear in limited space under the condition that the location of torso is ascertained. With this property, the SCGC can successfully remove false segmentations by traditional graph cuts methods due to their similar appearances to human body. Experimental results show that the proposed method achieves promising performance and outperforms many state-of-the-art methods over publicly available challenging datasets which contain arbitrary poses.