Rethinking random Hough Forests for video database indexing and pattern search
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[1] Matthieu Guillaumin,et al. Incremental Learning of Random Forests for Large-Scale Image Classification , 2016, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[2] Ebroul Izquierdo,et al. Minimal Hough Forest training for pattern detection , 2015, 2015 International Conference on Systems, Signals and Image Processing (IWSSIP).
[3] Ebroul Izquierdo,et al. On the impurity of street-scene video footage , 2015, ICDP.
[4] Juergen Gall,et al. Hough-based object detection with grouped features , 2014, 2014 IEEE International Conference on Image Processing (ICIP).
[5] Sinisa Todorovic,et al. Hough Forest Random Field for Object Recognition and Segmentation , 2013, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[6] Horst Bischof,et al. Hough-based tracking of non-rigid objects , 2011, 2011 International Conference on Computer Vision.
[7] Luc Van Gool,et al. Hough Forests for Object Detection, Tracking, and Action Recognition , 2011, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[8] Bastian Leibe,et al. Efficient object detection and segmentation with a cascaded Hough Forest ISM , 2011, 2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops).
[9] Luc Van Gool,et al. An Introduction to Random Forests for Multi-class Object Detection , 2011, Theoretical Foundations of Computer Vision.
[10] Gang Yu,et al. Unsupervised random forest indexing for fast action search , 2011, CVPR 2011.
[11] Luc Van Gool,et al. Backprojection Revisited: Scalable Multi-view Object Detection and Similarity Metrics for Detections , 2010, ECCV.
[12] Luc Van Gool,et al. Variations of a Hough-Voting Action Recognition System , 2010, ICPR Contests.
[13] Pushmeet Kohli,et al. On Detection of Multiple Object Instances Using Hough Transforms , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[14] 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.
[15] Luc Van Gool,et al. Using Multi-view Recognition and Meta-data Annotation to Guide a Robot's Attention , 2009, Int. J. Robotics Res..
[16] Juergen Gall,et al. Class-specific Hough forests for object detection , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.
[17] Bernt Schiele,et al. Robust Object Detection with Interleaved Categorization and Segmentation , 2008, International Journal of Computer Vision.
[18] G. Griffin,et al. Caltech-256 Object Category Dataset , 2007 .
[19] JUSTIN ZOBEL,et al. Inverted files for text search engines , 2006, CSUR.
[20] 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).
[21] Pietro Perona,et al. Learning Generative Visual Models from Few Training Examples: An Incremental Bayesian Approach Tested on 101 Object Categories , 2004, 2004 Conference on Computer Vision and Pattern Recognition Workshop.
[22] L. Breiman. Random Forests , 2001, Encyclopedia of Machine Learning and Data Mining.
[23] Geoff Hulten,et al. Mining high-speed data streams , 2000, KDD '00.
[24] Luc Van Gool,et al. Sparsity Potentials for Detecting Objects with the Hough Transform , 2012, BMVC.
[25] N. Yokoya,et al. 2020 Index IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing Vol. 13 , 2020, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.