Abstract
We present a method for tracking people in monocular broadcast sports videos by coupling a particle filter with a vote-based confidence map of athletes, appearance features and optical flow for motion estimation. The confidence map provides a continuous estimate of possible target locations in each frame and outperforms tracking with discrete target detections. We demonstrate the tracker on sports videos, tracking fast and articulated movements of athletes such as divers and gymnasts and on non-sports videos, tracking pedestrians in a PETS2009 sequence.
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References
Kang, J., Cohen, I., Medioni, G.: Soccer player tracking across uncalibrated camera streams. In: IEEE International Workshop on Visual Surveillance and Performance Evaluation of Tracking and Surveillance, VS-PETS (2003)
Choi, K., Seo, Y., Lee, S.: Probabilistic tracking of soccer players and ball. In: ACCV (2004)
Okuma, K., Taleghani, A., de Freitas, N., Little, J., Lowe, D.: A boosted particle filter: Multitarget detection and tracking. In: Pajdla, T., Matas, J(G.) (eds.) ECCV 2004. LNCS, vol. 3021, pp. 28–39. Springer, Heidelberg (2004)
Kristan, M., Pers, J., Perse, M., Kovacic, S.: Closed-world tracking of multiple interacting targets for indoor-sports applications. CVIU 113(5), 598–611 (2009)
Breitenstein, M., Reichlin, F., Leibe, B., Koller-Meier, E., Gool, L.V.: Robust tracking-by-detection using a detector confidence particle filter. In: ICCV (2009)
Hess, R., Fern, A.: Discriminatively trained particle filters for complex multi-object tracking. In: CVPR (2009)
Doucet, A., Freitas, N.D., Gordon, N. (eds.): Sequential Monte Carlo Methods in Practice. Springer, New York (2001)
Gall, J., Lempitsky, V.: Class-specific hough forests for object detection. In: CVPR (2009)
Rodriguez, M.D., Ahmed, J., Shah, M.: Action mach a spatio-temporal maximum average correlation height filter for action recognition. In: CVPR (2008)
Ferryman, J., Shahrokni, A.: Pets2009: Dataset and challenge. In: IEEE International Workshop on Performance Evaluation of Tracking and Surveillance (2009)
Sullivan, J., Carlsson, S.: Tracking and labelling of interacting multiple targets. In: Leonardis, A., Bischof, H., Pinz, A. (eds.) ECCV 2006. LNCS, vol. 3952, pp. 232–244. Springer, Heidelberg (2006)
Lu, W.L., Little, J.J.: Tracking and recognizing actions at a distance. In: Proceedings of the ECCV Workshop on Computer Vision Based Analysis in Sport Environments (CVBASE 2006), Graz, Austria (May 2006)
Liu, G., Tang, X., Cheng, H.D., Huang, J., Liu, J.: A novel approach for tracking high speed skaters in sports using a panning camera. Pattern Recogn. 42(11), 2922–2935 (2009)
Khatoonabadi, S.H., Rahmati, M.: Automatic soccer players tracking in goal scenes by camera motion elimination. Image Vision Comput. 27(4), 469–479 (2009)
Collins, R., Liu, Y., Leordeanu, M.: On-line selection of discriminative tracking features. TPAMI 27(1), 1631 (2005)
Grabner, H., Leistner, C., Bischof, H.: Semi-supervised on-line boosting for robust tracking. In: Forsyth, D., Torr, P., Zisserman, A. (eds.) ECCV 2008, Part I. LNCS, vol. 5302, pp. 234–247. Springer, Heidelberg (2008)
Babenko, B., Yang, M.H., Belongie, S.: Visual tracking with online multiple instance learning. In: CVPR (2009)
Andriluka, M., Roth, S., Schiele, B.: People-tracking-by-detection and people-detection-by-tracking. In: CVPR (2008)
Leibe, B., Leonardis, A., Schiele, B.: Robust object detection with interleaved categorization and segmentation. IJCV 77(1-3), 259–289 (2008)
Adam, A., Rivlin, E., Shimshoni, I.: Robust fragments-based tracking using the integral histogram. In: CVPR (2006)
Dalal, N., Triggs, B.: Histograms of oriented gradients for human detection. In: CVPR (2005)
Ojala, T., Pietikainen, M., Maenpaa, T.: Multiresolution gray-scale and rotation invariant texture classification with local binary patterns. TPAMI 24(7), 971–987 (2002)
Brox, T., Bruhn, A., Papenberg, N., Weickert, J.: High accuracy optical flow estimation based on a theory for warping. In: Pajdla, T., Matas, J(G.) (eds.) ECCV 2004. LNCS, vol. 3024, pp. 25–36. Springer, Heidelberg (2004)
Everingham, M., Van Gool, L., Williams, C.K.I., Winn, J., Zisserman, A.: The PASCAL Visual Object Classes Challenge, VOC 2007 Results (2007), http://www.pascal-network.org/challenges/VOC/voc2007/workshop/index.html
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Yao, A., Uebersax, D., Gall, J., Van Gool, L. (2010). Tracking People in Broadcast Sports. In: Goesele, M., Roth, S., Kuijper, A., Schiele, B., Schindler, K. (eds) Pattern Recognition. DAGM 2010. Lecture Notes in Computer Science, vol 6376. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15986-2_16
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DOI: https://doi.org/10.1007/978-3-642-15986-2_16
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