Computer Vision in Sports

Computer vision has a lot to offer the world of sports, for the competitors, organizers and viewers. This chapter sets the scene for this book, by outlining some of these applications, giving examples of what is already being used, and referring to the relevant chapters later in the book where current research is presented. It then goes on to discuss the main themes covered by these chapters, and how they relate to each other.

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[28]  Cordelia Schmid,et al.  Action recognition by dense trajectories , 2011, CVPR 2011.

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

[31]  Narendra Ahuja,et al.  Robust multi-object tracking via cross-domain contextual information for sports video analysis , 2012, 2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

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[34]  Pascal Fua,et al.  Multi-Commodity Network Flow for Tracking Multiple People , 2014, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[35]  Mubarak Shah,et al.  Spatiotemporal Deformable Part Models for Action Detection , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.

[36]  Yi Yang,et al.  Articulated pose estimation with flexible mixtures-of-parts , 2011, CVPR 2011.

[37]  David G. Lowe,et al.  Probabilistic Models of Appearance for 3-D Object Recognition , 2000, International Journal of Computer Vision.

[38]  Marcus A. Magnor,et al.  View and Time Interpolation in Image Space , 2008, Comput. Graph. Forum.

[39]  Mubarak Shah,et al.  Action MACH a spatio-temporal Maximum Average Correlation Height filter for action recognition , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.

[40]  Jan-Michael Frahm,et al.  Piecewise planar and non-planar stereo for urban scene reconstruction , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[41]  Hideo Saito,et al.  Intermediate view generation of soccer scene from multiple videos , 2001, Object recognition supported by user interaction for service robots.

[42]  Matej Kristan,et al.  Closed-world tracking of multiple interacting targets for indoor-sports applications , 2009, Comput. Vis. Image Underst..

[43]  Mohamed R. Amer,et al.  Multiobject tracking as maximum weight independent set , 2011, CVPR 2011.

[44]  Li Wang,et al.  Integrating local action elements for action analysis , 2012, Comput. Vis. Image Underst..

[45]  Du Tran,et al.  Human Activity Recognition with Metric Learning , 2008, ECCV.

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[47]  Bruce A. Draper,et al.  Scalable action recognition with a subspace forest , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.

[48]  Yaser Sheikh,et al.  Representing and Discovering Adversarial Team Behaviors Using Player Roles , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.

[49]  Ying Wang,et al.  Human Activity Recognition Based on R Transform , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.

[50]  Ming-Hsuan Yang,et al.  Top-down visual saliency via joint CRF and dictionary learning , 2012, CVPR.

[51]  Takeo Kanade,et al.  Tracking in unstructured crowded scenes , 2009, 2009 IEEE 12th International Conference on Computer Vision.

[52]  Frédéric Jurie,et al.  Sampling Strategies for Bag-of-Features Image Classification , 2006, ECCV.

[53]  Pascal Fua,et al.  Tracking multiple people under global appearance constraints , 2011, 2011 International Conference on Computer Vision.

[54]  Hui Cheng,et al.  Evaluation of low-level features and their combinations for complex event detection in open source videos , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.

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[56]  Iasonas Kokkinos,et al.  Discovering discriminative action parts from mid-level video representations , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.

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[58]  Ramakant Nevatia,et al.  Multi-target tracking by online learning of non-linear motion patterns and robust appearance models , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.

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[60]  Konrad Schindler,et al.  Discrete-continuous optimization for multi-target tracking , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.

[61]  Wen Gao,et al.  Mining Layered Grammar Rules for Action Recognition , 2011, International Journal of Computer Vision.

[62]  Loong Fah Cheong,et al.  Activity recognition using dense long-duration trajectories , 2010, 2010 IEEE International Conference on Multimedia and Expo.

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[64]  Wojciech Matusik,et al.  3D TV: a scalable system for real-time acquisition, transmission, and autostereoscopic display of dynamic scenes , 2004, ACM Trans. Graph..

[65]  Frank Dellaert,et al.  An MCMC-Based Particle Filter for Tracking Multiple Interacting Targets , 2004, ECCV.

[66]  Rama Chellappa,et al.  Sparse dictionary-based representation and recognition of action attributes , 2011, 2011 International Conference on Computer Vision.

[67]  Robert T. Collins,et al.  Multitarget data association with higher-order motion models , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.

[68]  Marc'Aurelio Ranzato,et al.  Efficient Learning of Sparse Representations with an Energy-Based Model , 2006, NIPS.

[69]  Lior Wolf,et al.  Local Trinary Patterns for human action recognition , 2009, 2009 IEEE 12th International Conference on Computer Vision.

[70]  Ying Wu,et al.  Collaborative tracking of multiple targets , 2004, CVPR 2004.

[71]  Dong Xu,et al.  Action recognition using context and appearance distribution features , 2011, CVPR 2011.

[72]  Koen E. A. van de Sande,et al.  Selective Search for Object Recognition , 2013, International Journal of Computer Vision.

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[74]  Cordelia Schmid,et al.  Evaluation of Local Spatio-temporal Features for Action Recognition , 2009, BMVC.

[75]  Irfan A. Essa,et al.  Motion fields to predict play evolution in dynamic sport scenes , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[76]  Robert C. Bolles,et al.  Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography , 1981, CACM.

[77]  Luc Van Gool,et al.  You'll never walk alone: Modeling social behavior for multi-target tracking , 2009, 2009 IEEE 12th International Conference on Computer Vision.

[78]  James J. Little,et al.  Identifying players in broadcast sports videos using conditional random fields , 2011, CVPR 2011.

[79]  Richard Szeliski,et al.  Piecewise planar stereo for image-based rendering , 2009, 2009 IEEE 12th International Conference on Computer Vision.

[80]  A. G. Amitha Perera,et al.  Multi-Object Tracking Through Simultaneous Long Occlusions and Split-Merge Conditions , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

[81]  Derek Bradley,et al.  Markerless garment capture , 2008, SIGGRAPH 2008.

[82]  Adam Finkelstein,et al.  The Generalized PatchMatch Correspondence Algorithm , 2010, ECCV.

[83]  Krystian Mikolajczyk,et al.  Action recognition with motion-appearance vocabulary forest , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.