Human limb segmentation in depth maps based on spatio-temporal Graph-cuts optimization

Journal of Ambient Intelligence and Smart Environments

Volumn 4, Issue 6, 2012, Pages 535-546

  Hernández Vela, Antonio ^a,b   Zlateva, Nadezhda ^c   Marinov, Alexander ^c   Reyes, Miguel ^a,b   Radeva, Petia ^a,b   Dimov, Dimo ^c   Escalera, Sergio ^a,b  

^a Barcelona Perception Computing Lab   (Spain)

^b UNIVERSITY OF BARCELONA   (Spain)

^c INSTITUTE OF INFORMATION AND COMMUNICATION TECHNOLOGIES   (Bulgaria)

Author keywords

Graph cuts; human body segmentation; multi label segmentation; Multi modal vision processing; Random Forest

Indexed keywords

GRAPH-CUTS; HUMAN BODIES; MULTI-LABEL; RANDOM FORESTS; VISION PROCESSING;

DECISION TREES;

GRAPHIC METHODS;

EID: 84872301788     PISSN: 18761364     EISSN: None     Source Type: Journal    
DOI: 10.3233/AIS-2012-0176     Document Type: Article

References (29)

1. Code laboratories cl nui platform-kinect driver/sdk, http:// codelaboratories.com/nui/.
2. Flexible action and articulated skeleton toolkit (faast), http://projects.ict.usc.edu/mxr/faast/.
3. Nite middleware, http://www.primesense.com/?p=515.
4. Openkinect (libfreenect), http://openkinect.org.
5. Openni, http://www.openni.org.
6. PrimesensorTM, http://www.primesense.com/?p=514.
7. Kinect for windows sdk from microsoft research, http://research. microsoft.com/en-us/um/redmond/projects/kinectsdk/.
8. Y. Boykov, O.Veksler and R. Zabih, Fast approximate energy minimization via graph cuts, IEEE Trans. Pattern Anal. Mach. Intell. 23 (November 2001), 1222-1239. ISSN 0162-8828.
9. Y. Boykov and G. Funka-Lea, Graph cuts and efficient n-d image segmentation, International Journal on Computer Vision 70 (2006), 109-131. ISSN 0920-5691.
10. G. Cheung, T. Kanade, J.-Y. Bouguet and M. Holler, A real time system for robust 3d voxel reconstruction of human motions in: IEEE Conference on Computer Vision and Pattern Recognition, Vol. 2, Hilton Head Island, USA, 2000, pp. 714-720.
11. N. Dalal and B. Triggs, Histogram of oriented gradients for human detection, Vol. 2, 2005, pp. 886-893.
12. N. Dalal, B. Triggs and C. Schmid, Human detection using oriented histograms of flow and appearance, in: European Conference on Computer Vision, 2006, pp. 7-13.
13. T. Darrell, G. Gordon, J. Woodfill and M. Harville, Integrated person tracking using stereo, color, and pattern detection, in: IEEE Conference on Computer Vision and Pattern Recognition, Santa Barbara, 1998, pp. 601-608.
14. J. Demšar, Statistical comparisons of classifiers over multiple data sets, J. Mach. Learn. Res. 7 (December 2006), 1-30. ISSN 1532-4435.
15. V. Ganapathi, C. Plagemann, D. Koller and S. Thrun, Real time motion capture using a single time-of-flight camera, in: IEEE Conference on Computer Vision and Pattern Recognition, 2010, pp. 755-762.
16. L. Grady, Random walks for image segmentation, IEEE Trans. Pattern Anal. Mach. Intell. 28(11) (November 2006), 1768-1783. ISSN 0162-8828.
17. A. Hernandez, M. Reyes, S. Escalera and P. Radeva, Spatiotemporal grabcut human segmentation for face and pose recovery, in: Computer Vision and Pattern Recognition Workshops (CVPRW), 2010 IEEE Computer Society Conference, on June 2010, pp. 33-40. doi:10.1109/CVPRW.2010.5543824.
18. L. Igual, J.C. Soliva, A Hernandez-Vela, S Escalera, X. Jimenez, O. Vilarroya and P. Radeva, A fully-automatic caudate nucleus segmentation of brain mri: Application in volumetric analysis of pediatric attention-deficit/ hyperactivity disorder, 10(105) (December 2011). doi:10.1186/1475-925X-10-105.
19. HP. Jain and A. Subramanian, Real-time upper-body human pose estimation using a depth camera, HP Technical Reports 1(190) (2010).
20. Y. Liu, C. Stoll, J. Gall, H.-P. Seidel and Theobalt C., Markerless motion capture of interacting characters using multi-view image segmentation, IEEE Conference on Computer Vision and Pattern Recognition 14(1) (2011), 1249-1256.
21. J. Rodgers, D. Anguelov, H.-C. Pang and D. Koller, Object pose detection in range scan data, in: IEEE Conference on Computer Vision and Pattern Recognition, 2006, pp. 2445-2452.
22. C. Rother, V. Kolmogorov and A. Blake, Grabcut: Interactive foreground extraction using iterated graph cuts, ACM SIGGRAPH 2004 Papers (2004), 309-314.
23. B. Sabata, F. Arman and J.K. Aggarwal, Segmentation of 3d range images using pyramidal data structures. CVGIP: Image Understanding 57(3) (1993), 373-387.
24. W. Schwartz, A. Kembhavi, D. Harwood and L. Davis, Human detection using partial least squares, in: International Conference on Computer Vision, 2009, pp. 24-31.
25. J. Shotton, A. Fitzgibbon, M. Cook, T. Sharp, M. Finocchio, R. Moore, A. Kipman and A. Blake, Real-time human pose recognition in parts from single depth images, in: IEEE Conference on Computer Vision and Pattern Recognition, 2011, pp. 1297-1304.
26. L. Breiman Statistics and L. Breiman, Random forests, in: Machine Learning, 2001, pp. 5-32.
27. E. Suma, B. Lange, A. Rizzo, D.M. Krum and M. Bolas, FAAST: The flexible action and articulated skeleton toolkit, in: IEEE Virtual Reality, Singapore, March 2011, pp. 245-246.
28. B. Dariush Y. Zhu and K. Fujimura, Controlled human pose estimation from depth image streams, in: Computer Vision and Pattern RecognitionWorkshop on TOF Computer Vision, 2008, pp. 1-8.
29. HD. Yang and S.W. Lee, Reconstruction of 3d human body pose from stereo image sequences based on top-down learning, Pattern Recognition 40(11) 2007, 3120-3131.