Identifying players in broadcast sports videos using conditional random fields

We are interested in the problem of automatic tracking and identification of players in broadcast sport videos shot with a moving camera from a medium distance. While there are many good tracking systems, there are fewer methods that can identify the tracked players. Player identification is challenging in such videos due to blurry facial features (due to fast camera motion and low-resolution) and rarely visible jersey numbers (which, when visible, are deformed due to player movements). We introduce a new system consisting of three components: a robust tracking system, a robust person identification system, and a conditional random field (CRF) model that can perform joint probabilistic inference about the player identities. The resulting system is able to achieve a player recognition accuracy up to 85% on unlabeled NBA basketball clips.

[1]  Alberto Del Bimbo,et al.  Automatic detection of player's identity in soccer videos using faces and text cues , 2006, MM '06.

[2]  T. Başar,et al.  A New Approach to Linear Filtering and Prediction Problems , 2001 .

[3]  Matthijs C. Dorst.  Distinctive Image Features from Scale-Invariant Keypoints , 2011 .

[4]  Radford M. Neal.  Pattern Recognition and Machine Learning , 2007, Technometrics.

[5]  Jiri Matas,et al.  Robust wide-baseline stereo from maximally stable extremal regions , 2004, Image Vis. Comput..

[6]  Simon Haykin,et al.  GradientBased Learning Applied to Document Recognition , 2001 .

[7]  Michael I. Jordan,et al.  Loopy Belief Propagation for Approximate Inference: An Empirical Study , 1999, UAI.

[8]  David G. Lowe,et al.  Shape Descriptors for Maximally Stable Extremal Regions , 2007, 2007 IEEE 11th International Conference on Computer Vision.

[9]  Mubarak Shah,et al.  Modeling inter-camera space-time and appearance relationships for tracking across non-overlapping views , 2008, Comput. Vis. Image Underst..

[10]  David J. Fleet,et al.  3D People Tracking with Gaussian Process Dynamical Models , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

[11]  Alberto Del Bimbo,et al.  Soccer players identification based on visual local features , 2007, CIVR '07.

[12]  Alexei A. Efros,et al.  Discovering objects and their location in images , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.

[13]  Yoshua Bengio,et al.  Gradient-based learning applied to document recognition , 1998, Proc. IEEE.

[14]  David A. McAllester,et al.  A discriminatively trained, multiscale, deformable part model , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.

[15]  Barbara Caputo,et al.  Who's Doing What: Joint Modeling of Names and Verbs for Simultaneous Face and Pose Annotation , 2009, NIPS.

[16]  D. Rubin,et al.  Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper , 1977 .

[17]  Wen Gao,et al.  Jersey number detection in sports video for athlete identification , 2005, Visual Communications and Image Processing.

[18]  Robert T. Collins,et al.  Multi-target Data Association by Tracklets with Unsupervised Parameter Estimation , 2008, BMVC.

[19]  B. Taskar,et al.  Learning from ambiguously labeled images , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.

[20]  Hrvoje Dujmić,et al.  Player Number Localization and Recognition in Soccer Video using HSV Color Space and Internal Contours , 2008 .

[21]  Andrew McCallum,et al.  Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data , 2001, ICML.

[22]  Hai Tao,et al.  Viewpoint Invariant Pedestrian Recognition with an Ensemble of Localized Features , 2008, ECCV.

[23]  A. Ng.  Feature selection, L1 vs. L2 regularization, and rotational invariance , 2004, Twenty-first international conference on Machine learning - ICML '04.

[24]  Robert A. Jacobs,et al.  Hierarchical Mixtures of Experts and the EM Algorithm , 1993, Neural Computation.

[25]  Alessandro Perina,et al.  Person re-identification by symmetry-driven accumulation of local features , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[26]  James J. Little,et al.  Robust Visual Tracking for Multiple Targets , 2006, ECCV.

[27]  James J. Little,et al.  A Boosted Particle Filter: Multitarget Detection and Tracking , 2004, ECCV.

[28]  Alberto Del Bimbo,et al.  Player identification in soccer videos , 2005, MIR '05.

[29]  Jia Liu,et al.  Automatic Player Detection, Labeling and Tracking in Broadcast Soccer Video , 2007, BMVC.