A dynamic conditional random field model for joint labeling of object and scene classes

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

Volumn 5305 LNCS, Issue PART 4, 2008, Pages 733-747

  Wojek, Christian ^a   Schiele, Bernt ^a  

^a DARMSTADT UNIVERSITY OF TECHNOLOGY   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER VISION; IMAGE SEGMENTATION; OBJECT RECOGNITION; PIXELS; PROFITABILITY; RANDOM PROCESSES;

CONDITIONAL RANDOM FIELD; DYNAMIC CONDITIONAL RANDOM FIELDS; DYNAMIC INFORMATION; DYNAMIC SCENES; OBJECT AND SCENES; OBJECT MOVEMENTS; REAL WORLD VIDEOS; SYSTEM COMPONENTS;

OBJECT DETECTION;

EID: 57149143156     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-88693-8_54     Document Type: Conference Paper

References (27)

1. Everingham, M., Zisserman, A., Williams, C., van Gool, L.: The pascal visual object classes challenge results. Technical report, PASCAL Network (2006)
2. Torralba, A.: Contextual priming for object detection. IJCV, 169-191 (2003)
3. Hoiem, D., Efros, A.A., Hebert, M.: Putting objects in perspective. In: CVPR (2006)
4. He, X., Zemel, R.S., Carreira-Perpiñán, M.Á.: Multiscale conditional random fields for image labeling. In: CVPR (2004)
5. Kumar, S., Hebert, M.: A hierarchical field framework for unified context-based classification. In: ICCV (2005)
6. Shotton, J., Winn, J., Rother, C., Criminisi, A.: Textonboost: Joint appearance, shape and context modeling for multi-class object recognition and segmentation. In: Leonardis, A., Bischof, H., Pinz, A. (eds.) ECCV 2006. LNCS, vol. 3951. Springer, Heidelberg (2006)
7. Torralba, A., Murphy, K.P., Freeman, W.T.: Contextual models for object detection using boosted random fields. In: NIPS (2004)
8. McCallum, A., Rohanimanesh, K., Sutton, C.: Dynamic conditional random fields for jointly labeling multiple sequences. In: NIPS Workshop on Syntax, Semantics (2003)
9. Lafferty, J.D., McCallum, A., Pereira, F.C.N.: Conditional random fields: Probabilistic models for segmenting and labeling sequence data. In: ICML (2001)
10. Kumar, S., Hebert, M.: Discriminative random fields: A discriminative framework for contextual interaction in classification. In: ICCV (2003)
11. Dalal, N., Triggs, B.: Histograms of oriented gradients for human detection. In: CVPR (2005)
12. Verbeek, J., Triggs, B.: Region classification with markov field aspect models. In: CVPR (2007)
13. Quattoni, A., Collins, M., Darrell, T.: Conditional random fields for object recognition. In: NIPS (2004)
14. Kapoor, A., Winn, J.: Located hidden random fields: Learning discriminative parts for object detection. In: Leonardis, A., Bischof, H., Pinz, A. (eds.) ECCV 2006. LNCS, vol. 3954. Springer, Heidelberg (2006)
15. Winn, J., Shotton, J.: The layout consistent random field for recognizing and segmenting partially occluded objects. In: CVPR (2006)
16. Wang, Y., Ji, Q.: A dynamic conditional random field model for object segmentation in image sequences. In: CVPR (2005)
17. Yin, Z., Collins, R.: Belief propagation in a 3D spatio-temporal MRF for moving object detection. In: CVPR (2007)
18. Leibe, B., Cornelis, N., Cornelis, K., Van Gool, L.: Dynamic 3D scene analysis from a moving vehicle. In: CVPR (2007)
19. Torralba, A., Murphy, K.P., Freeman, W.T.: Sharing features: Efficient boosting procedures for multiclass object detection. In: CVPR (2004)
20. Piatt, J.: Probabilistic outputs for support vector machines and comparison to regularized likelihood methods. In: Smola, A.J., Bartlett, P., Schoelkopf, B., Schuurmans, D. (eds.) Advances in Large Margin Classifiers, pp. 61-74 (2000)
21. Kalman, R.E.: A new approach to linear filtering and prediction problems. Transactions of the ASME-Journal of Basic Engineering 82, 35-45 (1960)
22. Sutton, C., McCallum, A.: Piecewise training for undirected models. In: 21th Annual Conference on Uncertainty in Artificial Intelligence (UAI 2005) (2005)
23. Vishwanathan, S.V.N., Schraudolph, N.N., Schmidt, M.W., Murphy, K.P.: Accelerated training of conditional random fields with stochastic gradient methods. In: ICML (2006)
24. Hel-Or, Y., Hel-Or, H.: Real-time pattern matching using projection kernels. PAMI 27, 1430-1445 (2005)
25. Alon, Y., Ferencz, A., Shashua, A.: Off-road path following using region classification and geometric projection constraints. In: CVPR (2006)
26. Varma, M., Zisserman, A.: Classifying images of materials: Achieving viewpoint and illumination independence. In: Tistarelli, M., Bigun, J., Jain, A.K. (eds.) ECCV 2002. LNCS, vol. 2359. Springer, Heidelberg (2002)
27. Russell, B.C., Torralba, A., Murphy, K.P., Freeman, W.T.: LabelMe: A database and web-based tool for image annotation. IJCV 77, 157-173 (2008)