Hough Forests for Object Detection, Tracking, and Action Recognition
暂无分享,去创建一个
Luc Van Gool | Juergen Gall | Angela Yao | Victor S. Lempitsky | Nima Razavi | L. Gool | Juergen Gall | V. Lempitsky | N. Razavi | Angela Yao | Nima Razavi
[1] Richard O. Duda,et al. Use of the Hough transformation to detect lines and curves in pictures , 1972, CACM.
[2] Dana H. Ballard,et al. Generalizing the Hough transform to detect arbitrary shapes , 1981, Pattern Recognit..
[3] Michael Isard,et al. Contour Tracking by Stochastic Propagation of Conditional Density , 1996, ECCV.
[4] Yali Amit,et al. Shape Quantization and Recognition with Randomized Trees , 1997, Neural Computation.
[5] Jiri Matas,et al. On Combining Classifiers , 1998, IEEE Trans. Pattern Anal. Mach. Intell..
[6] Nando de Freitas,et al. Sequential Monte Carlo Methods in Practice , 2001, Statistics for Engineering and Information Science.
[7] Shimon Ullman,et al. Class-Specific, Top-Down Segmentation , 2002, ECCV.
[8] B. Schiele,et al. Interleaved Object Categorization and Segmentation , 2003, BMVC.
[9] Andrew Zisserman,et al. Video Google: a text retrieval approach to object matching in videos , 2003, Proceedings Ninth IEEE International Conference on Computer Vision.
[10] Ivan Laptev,et al. On Space-Time Interest Points , 2003, Proceedings Ninth IEEE International Conference on Computer Vision.
[11] Leo Breiman,et al. Random Forests , 2001, Machine Learning.
[12] Takeo Kanade,et al. Object Detection Using the Statistics of Parts , 2004, International Journal of Computer Vision.
[13] Paul A. Viola,et al. Robust Real-Time Face Detection , 2001, International Journal of Computer Vision.
[14] B. Caputo,et al. Recognizing human actions: a local SVM approach , 2004, Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004..
[15] Dan Roth,et al. Learning to detect objects in images via a sparse, part-based representation , 2004, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[16] Gabriela Csurka,et al. Visual categorization with bags of keypoints , 2002, eccv 2004.
[17] Ronen Basri,et al. Actions as space-time shapes , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.
[18] Raphaël Marée,et al. Random subwindows for robust image classification , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).
[19] Pietro Perona,et al. Learning object categories from Google's image search , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.
[20] Frédéric Jurie,et al. Creating efficient codebooks for visual recognition , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.
[21] Serge J. Belongie,et al. Behavior recognition via sparse spatio-temporal features , 2005, 2005 IEEE International Workshop on Visual Surveillance and Performance Evaluation of Tracking and Surveillance.
[22] Bill Triggs,et al. Histograms of oriented gradients for human detection , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).
[23] Vincent Lepetit,et al. Randomized trees for real-time keypoint recognition , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).
[24] i-LIDS Team,et al. Imagery Library for Intelligent Detection Systems (i-LIDS); A Standard for Testing Video Based Detection Systems , 2006, Proceedings 40th Annual 2006 International Carnahan Conference on Security Technology.
[25] Luc Van Gool,et al. Towards Multi-View Object Class Detection , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).
[26] Jianguo Zhang,et al. The PASCAL Visual Object Classes Challenge , 2006 .
[27] Ehud Rivlin,et al. Robust Fragments-based Tracking using the Integral Histogram , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).
[28] Horst Bischof,et al. Real-Time Tracking via On-line Boosting , 2006, BMVC.
[29] Chiou-Shann Fuh,et al. Segmenting Highly Articulated Video Objects with Weak-Prior Random Forests , 2006, ECCV.
[30] Bernt Schiele,et al. Cross-Articulation Learning for Robust Detection of Pedestrians , 2006, DAGM-Symposium.
[31] Bernt Schiele,et al. Multi-Aspect Detection of Articulated Objects , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).
[32] Frédéric Jurie,et al. Fast Discriminative Visual Codebooks using Randomized Clustering Forests , 2006, NIPS.
[33] Juan Carlos Niebles,et al. Unsupervised Learning of Human Action Categories Using Spatial-Temporal Words , 2006, BMVC.
[34] David G. Lowe,et al. Multiclass Object Recognition with Sparse, Localized Features , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).
[35] Jamie Shotton,et al. The Layout Consistent Random Field for Recognizing and Segmenting Partially Occluded Objects , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).
[36] Bernt Schiele,et al. Robust Object Detection with Interleaved Categorization and Segmentation , 2008, International Journal of Computer Vision.
[37] Cordelia Schmid,et al. Accurate Object Detection with Deformable Shape Models Learnt from Images , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.
[38] Luc Van Gool,et al. Dynamic 3D Scene Analysis from a Moving Vehicle , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.
[39] Cordelia Schmid,et al. Learning realistic human actions from movies , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.
[40] 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.
[41] Horst Bischof,et al. Semi-supervised On-Line Boosting for Robust Tracking , 2008, ECCV.
[42] Andrew Blake,et al. Efficiently Combining Contour and Texture Cues for Object Recognition , 2008, BMVC.
[43] Krystian Mikolajczyk,et al. Action recognition with motion-appearance vocabulary forest , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.
[44] Christoph H. Lampert,et al. Beyond sliding windows: Object localization by efficient subwindow search , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.
[45] Toby Sharp,et al. Implementing Decision Trees and Forests on a GPU , 2008, ECCV.
[46] Antonio Criminisi,et al. Object Class Segmentation using Random Forests , 2008, BMVC.
[47] Luc Van Gool,et al. Action snippets: How many frames does human action recognition require? , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.
[48] Subhransu Maji,et al. Classification using intersection kernel support vector machines is efficient , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.
[49] Andrew Zisserman,et al. Learning an Alphabet of Shape and Appearance for Multi-Class Object Detection , 2008, International Journal of Computer Vision.
[50] Andrew Blake,et al. Multiscale Categorical Object Recognition Using Contour Fragments , 2008, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[51] Stefan Roth,et al. People-tracking-by-detection and people-detection-by-tracking , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.
[52] Roberto Cipolla,et al. Semantic texton forests for image categorization and segmentation , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.
[53] Cordelia Schmid,et al. Viewpoint-independent object class detection using 3D Feature Maps , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.
[54] Jitendra Malik,et al. Object detection using a max-margin Hough transform , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.
[55] Juergen Gall,et al. Class-specific Hough forests for object detection , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.
[56] Serge J. Belongie,et al. Visual tracking with online Multiple Instance Learning , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.
[57] Maja Pantic,et al. An implicit spatiotemporal shape model for human activity localization and recognition , 2009, 2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops.
[58] Larry S. Davis,et al. Recognizing actions by shape-motion prototype trees , 2009, 2009 IEEE 12th International Conference on Computer Vision.
[59] Lior Wolf,et al. Local Trinary Patterns for human action recognition , 2009, 2009 IEEE 12th International Conference on Computer Vision.
[60] Joachim M. Buhmann,et al. Seeing the Objects Behind the Dots: Recognition in Videos from a Moving Camera , 2009, International Journal of Computer Vision.
[61] Christoph H. Lampert,et al. Efficient Subwindow Search: A Branch and Bound Framework for Object Localization , 2009, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[62] S. Kollias,et al. Dense saliency-based spatiotemporal feature points for action recognition , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.
[63] Luc Van Gool,et al. Exemplar-based Action Recognition in Video , 2009, BMVC.
[64] Luc Van Gool,et al. The Pascal Visual Object Classes (VOC) Challenge , 2010, International Journal of Computer Vision.
[65] Mubarak Shah,et al. Incremental action recognition using feature-tree , 2009, 2009 IEEE 12th International Conference on Computer Vision.
[66] Moritz Tenorth,et al. The TUM Kitchen Data Set of everyday manipulation activities for motion tracking and action recognition , 2009, 2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV Workshops.
[67] Cordelia Schmid,et al. Evaluation of Local Spatio-temporal Features for Action Recognition , 2009, BMVC.
[68] Jiebo Luo,et al. Recognizing realistic actions from videos “in the wild” , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.
[69] Jitendra Malik,et al. Multi-scale object detection by clustering lines , 2009, 2009 IEEE 12th International Conference on Computer Vision.
[70] Ryuzo Okada,et al. Discriminative generalized hough transform for object dectection , 2009, 2009 IEEE 12th International Conference on Computer Vision.
[71] Mario Fritz,et al. Discriminative structure learning of hierarchical representations for object detection , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.
[72] B. Schiele,et al. Pictorial structures revisited: People detection and articulated pose estimation , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.
[73] David A. McAllester,et al. Object Detection with Discriminatively Trained Part Based Models , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[74] Zicheng Liu,et al. Cross-dataset action detection , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[75] Björn Ommer,et al. Voting by Grouping Dependent Parts , 2010, ECCV.
[76] Luc Van Gool,et al. Backprojection Revisited: Scalable Multi-view Object Detection and Similarity Metrics for Detections , 2010, ECCV.
[77] Horst Bischof,et al. PROST: Parallel robust online simple tracking , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[78] Luc Van Gool,et al. Fast PRISM: Branch and Bound Hough Transform for Object Class Detection , 2011, International Journal of Computer Vision.
[79] Luc Van Gool,et al. Tracking People in Broadcast Sports , 2010, DAGM-Symposium.
[80] David A. McAllester,et al. Cascade object detection with deformable part models , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[81] Adriana Kovashka,et al. Learning a hierarchy of discriminative space-time neighborhood features for human action recognition , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[82] Luc Van Gool,et al. On-line Adaption of Class-specific Codebooks for Instance Tracking , 2010, BMVC.
[83] Shimon Ullman,et al. The chains model for detecting parts by their context , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[84] Antonio Torralba,et al. Part and appearance sharing: Recursive Compositional Models for multi-view , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[85] Luc Van Gool,et al. A Hough transform-based voting framework for action recognition , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[86] Martial Hebert,et al. Representing Pairwise Spatial and Temporal Relations for Action Recognition , 2010, ECCV.
[87] Pushmeet Kohli,et al. On Detection of Multiple Object Instances Using Hough Transforms , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.