Joint classification-regression forests for spatially structured multi-object segmentation

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

Volumn 7575 LNCS, Issue PART 4, 2012, Pages 870-881

  Glocker, Ben ^a   Pauly, Olivier ^b,c   Konukoglu, Ender ^a   Criminisi, Antonio ^a  

^a MICROSOFT RESEARCH   (United Kingdom)

^b INSTITUTE OF EPIDEMIOLOGY   (Germany)

^c TECHNICAL UNIVERSITY OF MUNICH   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

ADDITIONAL COSTS; CLASS LABELS; DATA SETS; EXPERIMENTAL VALIDATIONS; FOREST MODELS; GROUND TRUTH; IMAGE POINTS; JOINT OBJECTIVE FUNCTION; LABELED IMAGES; MULTI-OBJECT SEGMENTATION; OBJECT BOUNDARIES; PIXEL CLASSIFICATION; SHAPE REGRESSION; SIGNED DISTANCE; SPATIAL ARRANGEMENTS; SPATIAL CONSISTENCY; STRUCTURAL INFORMATION;

FORESTRY; IMAGE CLASSIFICATION; REGRESSION ANALYSIS;

COMPUTER VISION;

ALGORITHMS; CLASSIFICATION; FORESTRY; IMAGE ANALYSIS; REGRESSION ANALYSIS;

EID: 84867866293     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-33765-9_62     Document Type: Conference Paper

References (21)

1. Breiman, L.: Random Forests. Machine Learning 45(1), 5-32 (2001)
2. Criminisi, A., Shotton, J., Konukoglu, E.: Decision Forests: A Unified Framework. Foundations and Trends in Computer Graphics and Vision 7(2-3) (2011)
3. Ho, T.K.: Random Decision Forests. In: ICDAR, vol. 1, pp. 278-282 (1995)
4. Ho, T.K.: The Random Subspace Method for Constructing Decision Forests. PAMI 20(8), 832-844 (1998)
5. Shotton, J., Fitzgibbon, A., Cook, M., Sharp, T., Finocchio, M., Moore, R., Kipman, A., Blake, A.: Real-Time Human Pose Recognition in Parts from a Single Depth Image. In: CVPR, pp. 1297-1304 (2011)
6. Amit, Y., Geman, D.: Shape Quantization and Recognition with Randomized Trees. Neural Computation 9, 1545-1588 (1997)
7. Criminisi, A., Shotton, J., Robertson, D., Konukoglu, E.: Regression Forests for Efficient Anatomy Detection and Localization in CT Studies. In: Menze, B., Langs, G., Tu, Z., Criminisi, A. (eds.) MICCAI 2010. LNCS, vol. 6533, pp. 106-117. Springer, Heidelberg (2011)
8. Bosch, A., Zisserman, A., Munoz, X.: Image Classification Using Random Forests and Ferns. In: ICCV (2007)
9. Maree, R., Geurts, P., Piater, J., Wehenkel, L.: Random Subwindows for Robust Image Classification. In: CVPR (2005)
10. Caruana, R., Karampatziakis, N., Yessenalina, A.: An Empirical Evaluation of Supervised Learning in High Dimensions. In: ICML, pp. 96-103 (2008)
11. Yin, P., Criminisi, A., Essa, I., Winn, J.: Tree-based Classifiers for Bilayer Video Segmentation. In: CVPR, pp. 1-8 (2007)
12. Payet, N., Todorovic, S.: (RF)2 Random Forest Random Field. In: NIPS (2010)
13. Kontschieder, P., Rota Buló, S., Bischof, H., Pelillo, M.: Structured class-labels in random forests for semantic image labelling. In: ICCV (2011)
14. Montillo, A., Shotton, J., Winn, J., Iglesias, J.E., Metaxas, D., Criminisi, A.: Entangled Decision Forests and Their Application for Semantic Segmentation of CT Images. In: Székely, G., Hahn, H.K. (eds.) IPMI 2011. LNCS, vol. 6801, pp. 184-196. Springer, Heidelberg (2011)
15. Nowozin, S., Rother, C., Bagon, S., Sharp, T., Yao, B., Kohli, P.: Decision Tree Fields. In: ICCV (2011)
16. Felzenszwalb, P.F., Huttenlocher, D.P.: Pictorial Structures for Object Recognition. IJCV 61(1), 55-79 (2005)
17. Girshick, R., Shotton, J., Kohli, P., Criminisi, A., Fitzgibbon, A.: Efficient Regression of General-Activity Human Poses from Depth Images. In: ICCV, pp. 415-422 (2011)
18. Gall, J., Yao, A., Razavi, N., Van Gool, L., Lempitsky, V.: Hough Forests for Object Detection, Tracking, and Action Recognition. PAMI 33(11), 2188-2202 (2011)
19. Cootes, T., Edwards, G., Taylor, C.: Active Appearance Models. PAMI 23(6), 681-685 (2001)
20. Boykov, Y., Funka-Lea, G.: Graph Cuts and Efficient N-D Image Segmentation. IJCV 70(2), 109-131 (2006)
21. Viola, P., Jones, M.J.: Robust Real-Time Face Detection. IJCV 57(2), 137-154 (2004)