Using linking features in learning non-parametric part models

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 7574 LNCS, Issue PART 3, 2012, Pages 326-339

  Karlinsky, Leonid ^a   Ullman, Shimon ^a  

^a WEIZMANN INSTITUTE OF SCIENCE   (Israel)

Author keywords

FLPM model; linking features; parts detection

Indexed keywords

DATA SETS; DEFORMABLE OBJECT; FIDUCIAL POINTS; HUMAN BODIES; JOINT CONFIGURATION; KINEMATIC CONSTRAINTS; LINKING FEATURES; NON-PARAMETRIC; TEST IMAGES; UPPER ARM;

DATA PROCESSING;

COMPUTER VISION;

EID: 84867865838     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-33712-3_24     Document Type: Conference Paper

References (21)

1. Felzenszwalb, P., Huttenlocher, D.: Pictorial structures for object recognition. IJCV (2005)
2. Ramanan, D.: Learning to parse images of articulated objects. In: NIPS (2006)
3. Eichner, M., Ferrari, V.: Better appearance models for pictorial structures. In: BMVC (2009)
4. Andriluka, M., Roth, S., Schiele, B.: Pictorial structures revisited: People detection and articulated pose estimation. In: CVPR (2009)
5. Wang, Y., Mori, G.: Multiple Tree Models for Occlusion and Spatial Constraints in Human Pose Estimation. In: Forsyth, D., Torr, P., Zisserman, A. (eds.) ECCV 2008, Part III. LNCS, vol. 5304, pp. 710-724. Springer, Heidelberg (2008)
6. Jiang, H., Martin, D.R.: Global pose estimation using non-tree models. In: CVPR (2008)
7. Yao, B., Fei-Fei, L.: Modeling mutual context of object and human pose in human-object interaction activities. In: CVPR (2010)
8. Sapp, B., Jordan, C., Taskar, B.: Adaptive pose priors for pictorial structures. In: CVPR (2010)
9. Sapp, B., Toshev, A., Taskar, B.: Cascaded Models for Articulated Pose Estimation. In: Daniilidis, K., Maragos, P., Paragios, N. (eds.) ECCV 2010, Part II. LNCS, vol. 6312, pp. 406-420. Springer, Heidelberg (2010)
10. Yang, Y., Ramanan, D.: Articulated pose estimation using flexible mixtures of parts. In: CVPR (2011)
11. Ioffe, S., Forsyth, D.: Human tracking with mixtures of trees. In: ICCV (2001)
12. Sapp, B., Weiss, D., Taskar, B.: Parsing human motion with stretchable models. In: CVPR (2011)
13. Bourdev, L., Malik, J.: Poselets: Body part detectors trained using 3d human pose annotations. In: ICCV (2009)
14. Karlinsky, L., Dinerstein, M., Harari, D., Ullman, S.: The chains model for detecting parts by their context. In: CVPR (2010)
15. Martinez, A., Benavente, R.: The ar face database. CVC Technical Report num. 24 (1998)
16. Ding, L., Martinez, A.M.: Features versus context: An approach for precise and detailed detection and delineation of faces and facial features. PAMI (2010)
17. Lowe, D.: Distinctive image features from scale-invariant keypoints. IJCV (2004)
18. Liu, C., Yuen, J., Torralba, A.: Sift flow: dense correspondence across different scenes and its applications. PAMI (2010)
19. Mount, D., Arya, S.: Ann: A library for approximate nearest neighbor searching. CGC (1997)
20. Duda, R., Hart, P.: Pattern classification and scene analysis. Wiley (1973)
21. Ng, A., Jordan, M., Weiss, Y.: On spectral clustering: Analysis and an algorithm. In: NIPS (2001)