Pérez, P., Hue, C., Vermaak, J., Gangnet, M.: Color-based probabilistic tracking. In: Heyden, A., Sparr, G., Nielsen, M., Johansen, P. (eds.) ECCV 2002. LNCS, vol. 2350, pp. 661-675. Springer, Heidelberg (2002)
Taylor, G., Kleeman, L.: Fusion of multimodal visual cues for model-based object tracking. In: acra (2003)
Özuysal, M., Lepetit, V., Fleuret, F., Fua, P.: Feature harvesting for tracking-by-detection. In: Leonardis, A., Bischof, H., Pinz, A. (eds.) ECCV 2006. LNCS, vol. 3953, pp. 592-605. Springer, Heidelberg (2006)
Yang, C., Duraiswami, R., Davis, L.: Fast multiple object tracking via a hierarchical particle filter. In: ICCV, Beijing, China (2005)
Pérez, P., Vermaak, J., Blake, A.: Data fusion for visual tracking with particles. Proceedings of the IEEE 92(3), 495-513 (2004)
Isard, M., Blake, A.: Condensation - conditional density propagation for visual tracking. International Journal of Computer Vision 29(2), 5-28 (1998)
Birchfield, S.: Elliptical head tracking using intensity gradients and color histograms. In: CVPR, Santa Barbara, CA, pp. 232-237 (1998)
Triesch, J., Malsburg, Cv.: Self-organized integration of adaptive visual cues for face tracking. In: The Fourth IEEE International Conference on Automatic Face and Gesture Recognition (2000)
Giebell, J., Gavrilal, D., Schnörr, C.: A bayesian framework for multi-cue 3d object tracking. In: Pajdla, T., Matas, J(G.) (eds.) ECCV 2004. LNCS, vol. 3024, pp. 241-252. Springer, Heidelberg (2004)
Leichter, I., Lindenbaum, M., Rivlin, E.: A general framework for combining visual trackers: The black boxes approach. IJCV 67(3), 343-363 (2006)
Wu, Y., Huang, T.: Robust visual tracking by integrating multiple cues based on co-inference learning. International Journal of Computer Vision 58(1), 55-71 (2004)
Brand, M.: Coupled hidden Markov models for modeling interacting processes. Technical report, MIT Media Lab Perceptual Computing (1997)
Brasnett, P., Mihaylova, L., Canagarajah, N., Bull, D.: Particle filtering with multiple cues for object tracking in video sequences. In: Proceeding of SPIE-Image and Video Communications, vol. 5685, pp. 430-441 (2005)
Wang, H., Suter, D.: Efficient visual tracking by probabilistic fusion of multiple cues. In: ICPR, HongKong (2006)
Spengler, M., Schiele, B.: Towards robust multi-cue integration for visual tracking. In: MVA, vol. 14, pp. 50-58 (2003)
Gavrila, D.M., Munder, S.: Multi-cue pedestrian detection and tracking from a moving vehicle. International Journal of Computer Vision (2007)
Sudderth, E., Ihler, A., Freeman, W., Willsky, A.: Nonparametric belief propagation. In: IEEE Conference on Computer Vision and Pattern Recognition, Madison, WI, vol. 2, pp. 605-612 (2003)
Isard, M.: Pampas: Real-valued graphical models for computer vision. In: IEEE Conference on Computer Vision and Pattern Recognition, Madison, WI, vol. 1, pp. 613-620 (2003)
Hua, G., Wu, Y.: Multi-scale visual tracking by sequential belief propagation. In: IEEE Conference on Computer Vision and Pattern Recognition, Washington, DC, vol. 1, pp. 826-833 (2004)
Briers, M., Doucet, A., Singh, S.: Sequential auxiliary particle belief propagation. In: The Eighth International Conference on Information Fusion (2005)
Sun, J., Zheng, N., Harry, S.: Stereo matching using belief propagation. IEEE Transactions on Pattern Analysis and Machine Intelligence 25(7), 787-800 (2003)
Birchfield, S.T., Rangarajan, S.: Spatiograms versus histograms for region-based tracking. In: IEEE Conference on Computer Vision and Pattern Recognition, San Diego, CA (2005)
Porkili, F.: Integral histogram: A fast way to extract histograms in cartesian spaces. In: CVPR, San Diego, CA (2005)
Wang, H., Suter, D., Schindler, K.: Effective appearance model and similarity measure for particle filtering and visual tracking. In: Leonardis, A., Bischof, H., Pinz, A. (eds.) ECCV 2006. LNCS, vol. 3953, pp. 606-618. Springer, Heidelberg (2006)