Survey of The Problem of Object Detection In Real Images
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[1] Hans P. Moravec. Rover Visual Obstacle Avoidance , 1981, IJCAI.
[2] Larry S. Davis,et al. Two-dimensional object recognition by matching local properties of contour points , 1984, Pattern Recognit. Lett..
[3] Gunilla Borgefors,et al. Hierarchical Chamfer Matching: A Parametric Edge Matching Algorithm , 1988, IEEE Trans. Pattern Anal. Mach. Intell..
[4] Christopher G. Harris,et al. A Combined Corner and Edge Detector , 1988, Alvey Vision Conference.
[5] Yoav Freund,et al. Boosting a weak learning algorithm by majority , 1995, COLT '90.
[6] Mandyam D. Srinath,et al. Partial Shape Classification Using Contour Matching in Distance Transformation , 1990, IEEE Trans. Pattern Anal. Mach. Intell..
[7] Frank C. D. Tsai. Robust affine invariant matching with application to line features , 1993, Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.
[8] Xueyin Lin,et al. A stereo matching algorithm based on shape similarity for indoor environment model building , 1996, Proceedings of IEEE International Conference on Robotics and Automation.
[9] Sharon X. Wang,et al. Model-based matching using elliptical features , 1996, Defense, Security, and Sensing.
[10] Fang-Hsuan Cheng,et al. Fast algorithm for point pattern matching: Invariant to translations, rotations and scale changes , 1997, Pattern Recognit..
[11] Clark F. Olson,et al. Automatic target recognition by matching oriented edge pixels , 1997, IEEE Trans. Image Process..
[12] Roberto Brunelli,et al. MASSACHUSETTS INSTITUTE OF TECHNOLOGY ARTIFICIAL INTELLIGENCE LABORATORY and CENTER FOR BIOLOGICAL AND COMPUTATIONAL LEARNING DEPARTMENT OF BRAIN AND COGNITIVE SCIENCES , 2001 .
[13] Andrea Salgian,et al. A cubist approach to object recognition , 1998, Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271).
[14] Yoram Singer,et al. Improved Boosting Algorithms Using Confidence-rated Predictions , 1998, COLT' 98.
[15] Fang-Hsuan Cheng. Multi-stroke relaxation matching method for handwritten chinese character recognition , 1998, Pattern Recognit..
[16] Yoav Freund,et al. An Adaptive Version of the Boost by Majority Algorithm , 1999, COLT '99.
[17] Jitendra Malik,et al. Matching Shapes , 2001, ICCV.
[18] J. Friedman. Greedy function approximation: A gradient boosting machine. , 2001 .
[19] Pedro F. Felzenszwalb. Learning models for object recognition , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.
[20] Tomaso A. Poggio,et al. Example-Based Object Detection in Images by Components , 2001, IEEE Trans. Pattern Anal. Mach. Intell..
[21] Dong-Gyu Sim,et al. Two-dimensional object alignment based on the robust oriented Hausdorff similarity measure , 2001, IEEE Trans. Image Process..
[22] Alfredo Petrosino,et al. The orientation matching approach to circular object detection , 2001, Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205).
[23] Yongsheng Gao,et al. Line segment Hausdorff distance on face matching , 2002, Pattern Recognit..
[24] J. Friedman. Stochastic gradient boosting , 2002 .
[25] Jiri Matas,et al. Robust wide-baseline stereo from maximally stable extremal regions , 2004, Image Vis. Comput..
[26] Bernt Schiele,et al. Analyzing appearance and contour based methods for object categorization , 2003, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings..
[27] Barbara Caputo,et al. Recognition with local features: the kernel recipe , 2003, Proceedings Ninth IEEE International Conference on Computer Vision.
[28] Peter Auer,et al. Weak Hypotheses and Boosting for Generic Object Detection and Recognition , 2004, ECCV.
[29] L. Gool,et al. Composite Texture Synthesis , 2005, International Journal of Computer Vision.
[30] Takeo Kanade,et al. Object Detection Using the Statistics of Parts , 2004, International Journal of Computer Vision.
[31] A. Torralba,et al. Sharing features: efficient boosting procedures for multiclass object detection , 2004, Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004..
[32] G LoweDavid,et al. Distinctive Image Features from Scale-Invariant Keypoints , 2004 .
[33] R. Sukthankar,et al. PCA-SIFT: a more distinctive representation for local image descriptors , 2004, Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004..
[34] Yongsheng Gao,et al. Hausdorff distance for shape matching , 2004 .
[35] David G. Lowe,et al. Probabilistic Models of Appearance for 3-D Object Recognition , 2000, International Journal of Computer Vision.
[36] Pietro Perona,et al. A Visual Category Filter for Google Images , 2004, ECCV.
[37] Clark F. Olson,et al. A General Method for Geometric Feature Matching and Model Extraction , 2001, International Journal of Computer Vision.
[38] Yanling Chi,et al. A Local Structure Matching Approach for Large Image Database Retrieval , 2004, ICIAR.
[39] 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.
[40] Paul A. Viola,et al. Robust Real-Time Face Detection , 2001, International Journal of Computer Vision.
[41] Yoram Singer,et al. Logistic Regression, AdaBoost and Bregman Distances , 2000, Machine Learning.
[42] 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.
[43] Paul A. Viola,et al. Boosting Image Retrieval , 2004, International Journal of Computer Vision.
[44] Horst Bischof,et al. Illumination insensitive recognition using eigenspaces , 2004, Comput. Vis. Image Underst..
[45] Stan Z. Li,et al. FloatBoost learning and statistical face detection , 2004, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[46] Daniel P. Huttenlocher,et al. Pictorial Structures for Object Recognition , 2004, International Journal of Computer Vision.
[47] Yali Amit,et al. A coarse-to-fine strategy for multiclass shape detection , 2004, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[48] Ayhan Demiriz,et al. Linear Programming Boosting via Column Generation , 2002, Machine Learning.
[49] Shimon Ullman,et al. Learning to Segment , 2004, ECCV.
[50] Saleh Basalamah,et al. Contrast Marginalised Gradient Template Matching , 2004, eccv 2004.
[51] Cordelia Schmid,et al. A maximum entropy framework for part-based texture and object recognition , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.
[52] Jitendra Malik,et al. Shape matching and object recognition using low distortion correspondences , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).
[53] Pietro Perona,et al. A sparse object category model for efficient learning and exhaustive recognition , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).
[54] Zhuowen Tu,et al. Probabilistic boosting-tree: learning discriminative models for classification, recognition, and clustering , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.
[55] Mubarak Shah,et al. A supervised learning framework for generic object detection in images , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.
[56] Guillaume Bouchard,et al. Hierarchical part-based visual object categorization , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).
[57] Paul A. Viola,et al. Detecting Pedestrians Using Patterns of Motion and Appearance , 2005, International Journal of Computer Vision.
[58] Zhuowen Tu,et al. Image Parsing: Unifying Segmentation, Detection, and Recognition , 2005, International Journal of Computer Vision.
[59] Shimon Ullman,et al. Feature hierarchies for object classification , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.
[60] Ilkay Ulusoy,et al. Generative versus discriminative methods for object recognition , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).
[61] Shimon Ullman,et al. Cross-generalization: learning novel classes from a single example by feature replacement , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).
[62] Cordelia Schmid,et al. A performance evaluation of local descriptors , 2005, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[63] Luc Van Gool,et al. Simultaneous Object Recognition and Segmentation from Single or Multiple Model Views , 2006, International Journal of Computer Vision.
[64] Pietro Perona,et al. Learning object categories from Google's image search , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.
[65] Jitendra Malik,et al. Efficient shape matching using shape contexts , 2005, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[66] Frédéric Jurie,et al. Creating efficient codebooks for visual recognition , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.
[67] Andrew Blake,et al. Contour-based learning for object detection , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.
[68] Pedro F. Felzenszwalb. Representation and detection of deformable shapes , 2003, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings..
[69] Daphna Weinshall,et al. Object class recognition by boosting a part-based model , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).
[70] Bernt Schiele,et al. Integrating representative and discriminant models for object category detection , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.
[71] Wei Zhang,et al. Object class recognition using multiple layer boosting with heterogeneous features , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).
[72] Daphna Weinshall,et al. Efficient Learning of Relational Object Class Models , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.
[73] Wen Gao,et al. Object detection using spatial histogram features , 2006, Image Vis. Comput..
[74] Tai-Hoon Cho. Object Matching Using Generalized Hough Transform and Chamfer Matching , 2006, PRICAI.
[75] Fang Li,et al. Two-stage Approach for Palmprint Identification using Hough Transform and Hausdorff Distance , 2006, 2006 9th International Conference on Control, Automation, Robotics and Vision.
[76] Luc Van Gool,et al. Object Detection by Contour Segment Networks , 2006, ECCV.
[77] Richard S. Zemel,et al. Learning Parts-Based Representations of Data , 2006, J. Mach. Learn. Res..
[78] Ramakant Nevatia,et al. Detection and Tracking of Multiple, Partially Occluded Humans by Bayesian Combination of Edgelet based Part Detectors , 2007, International Journal of Computer Vision.
[79] Juan José Rodríguez Diez,et al. Rotation Forest: A New Classifier Ensemble Method , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[80] James H. Elder,et al. Pre-Attentive and Attentive Detection of Humans in Wide-Field Scenes , 2007, International Journal of Computer Vision.
[81] Peter Auer,et al. Generic object recognition with boosting , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[82] Cordelia Schmid,et al. Beyond Bags of Features: Spatial Pyramid Matching for Recognizing Natural Scene Categories , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).
[83] Luc Van Gool,et al. Edinburgh Research Explorer Simultaneous Object Recognition and Segmentation by Image Exploration , 2022 .
[84] Duy-Dinh Le,et al. Ent-Boost: Boosting Using Entropy Measure for Robust Object Detection , 2006, ICPR.
[85] Zhuowen Tu,et al. Supervised Learning of Edges and Object Boundaries , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).
[86] P. Bickel,et al. Some Theory for Generalized Boosting Algorithms , 2006, J. Mach. Learn. Res..
[87] Shumeet Baluja,et al. Boosting Sex Identification Performance , 2005, International Journal of Computer Vision.
[88] Mark Culp,et al. and Development , 1998 .
[89] Cordelia Schmid,et al. Local Features and Kernels for Classification of Texture and Object Categories: A Comprehensive Study , 2006, 2006 Conference on Computer Vision and Pattern Recognition Workshop (CVPRW'06).
[90] Maylor K. H. Leung,et al. Shape Recognition using Curve Segment Hausdorff Distance , 2006, 18th International Conference on Pattern Recognition (ICPR'06).
[91] Jitendra Malik,et al. Shape Guided Object Segmentation , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).
[92] Andrew Zisserman,et al. Incremental learning of object detectors using a visual shape alphabet , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).
[93] Tom Minka,et al. Principled Hybrids of Generative and Discriminative Models , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).
[94] Bernt Schiele,et al. Multiple Object Class Detection with a Generative Model , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).
[95] 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).
[96] Antonio Criminisi,et al. TextonBoost for Image Understanding: Multi-Class Object Recognition and Segmentation by Jointly Modeling Texture, Layout, and Context , 2007, International Journal of Computer Vision.
[97] Fang Li,et al. A Two-Level Matching Scheme for Speedy and Accurate Palmprint Identification , 2007, MMM.
[98] Bernt Schiele,et al. Robust Object Detection with Interleaved Categorization and Segmentation , 2008, International Journal of Computer Vision.
[99] Yanling Chi,et al. Part-Based Object Retrieval in Cluttered Environment , 2007, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[100] Yuan Li,et al. High-Performance Rotation Invariant Multiview Face Detection , 2007, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[101] Shai Avidan,et al. Ensemble Tracking , 2005, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[102] Rama Chellappa,et al. Robust Estimation of Albedo for Illumination-invariant Matching and Shape Recovery , 2007, ICCV.
[103] Joseph J. LaViola,et al. A Practical Approach for Writer-Dependent Symbol Recognition Using a Writer-Independent Symbol Recognizer , 2007, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[104] Qiang Ji,et al. Multi-view face and eye detection using discriminant features , 2007, Comput. Vis. Image Underst..
[105] Cordelia Schmid,et al. Learning to Recognize Objects with Little Supervision , 2008, International Journal of Computer Vision.
[106] Jitendra Malik,et al. Learning Probabilistic Models for Contour Completion in Natural Images , 2008, International Journal of Computer Vision.
[107] Jamie Shotton,et al. Contour and Texture for Visual Recognition of Object Categories: Automatic Object Recognition Using Learned Patterns of Contour and Texture , 2007 .
[108] Joshua D. Schwartz,et al. Hierarchical Matching of Deformable Shapes , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.
[109] Antonio Torralba,et al. Sharing Visual Features for Multiclass and Multiview Object Detection , 2007, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[110] Arthur E. C. Pece,et al. On the computational rationale for generative models , 2007, Comput. Vis. Image Underst..
[111] Frédéric Jurie,et al. Groups of Adjacent Contour Segments for Object Detection , 2008, IEEE Trans. Pattern Anal. Mach. Intell..
[112] Naif Alajlan,et al. Geometry-Based Image Retrieval in Binary Image Databases , 2008, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[113] James M. Rehg,et al. Fast Asymmetric Learning for Cascade Face Detection , 2008, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[114] Sanja Fidler,et al. Selecting features for object detection using an AdaBoost-compatible evaluation function , 2008, Pattern Recognit. Lett..
[115] Roope Raisamo,et al. Evaluation of Gender Classification Methods with Automatically Detected and Aligned Faces , 2008, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[116] Long Zhu,et al. Unsupervised learning of probabilistic object models (POMs) for object classification, segmentation and recognition , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.
[117] Krystian Mikolajczyk,et al. Action recognition with motion-appearance vocabulary forest , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.
[118] Alfred M. Bruckstein,et al. Partial Similarity of Objects, or How to Compare a Centaur to a Horse , 2009, International Journal of Computer Vision.
[119] David Suter,et al. Object detection by global contour shape , 2008, Pattern Recognit..
[120] Margrit Betke,et al. Detecting Objects of Variable Shape Structure With Hidden State Shape Models , 2008, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[121] Jing Li,et al. A comprehensive review of current local features for computer vision , 2008, Neurocomputing.
[122] Andrew Zisserman,et al. Scene Classification Using a Hybrid Generative/Discriminative Approach , 2008, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[123] Florent Perronnin,et al. Universal and Adapted Vocabularies for Generic Visual Categorization , 2008, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[124] Andrew Zisserman,et al. Learning an Alphabet of Shape and Appearance for Multi-Class Object Detection , 2008, International Journal of Computer Vision.
[125] Andrew Blake,et al. Multiscale Categorical Object Recognition Using Contour Fragments , 2008, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[126] Atilla Baskurt,et al. 3D mirror symmetry detection using Hough transform , 2008, 2008 15th IEEE International Conference on Image Processing.
[127] Hwann-Tzong Chen,et al. Histogram-based interest point detectors , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.
[128] Tsuhan Chen,et al. Unsupervised learning of hierarchical spatial structures in images , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.
[129] Christoph H. Lampert,et al. Learning to detect unseen object classes by between-class attribute transfer , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.
[130] Nikolaos Papanikolopoulos,et al. Multi-class active learning for image classification , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.
[131] Arnold W. M. Smeulders,et al. What is the spatial extent of an object? , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.
[132] In-So Kweon,et al. Robust feature point matching by preserving local geometric consistency , 2009, Comput. Vis. Image Underst..
[133] Joseph J. Lim,et al. Recognition using regions , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.
[134] Jake Porway,et al. A Hierarchical and Contextual Model for Aerial Image Parsing , 2010, International Journal of Computer Vision.
[135] Jitendra Malik,et al. Object detection using a max-margin Hough transform , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.
[136] Juergen Gall,et al. Class-specific Hough forests for object detection , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.
[137] Christoph H. Lampert,et al. Active Structured Learning for High-Speed Object Detection , 2009, DAGM-Symposium.
[138] Fuguo Zhu,et al. Real-time object detection based on the improved boosted features , 2009, International Symposium on Multispectral Image Processing and Pattern Recognition.
[139] Gustavo Carneiro,et al. The quantitative characterization of the distinctiveness and robustness of local image descriptors , 2009, Image Vis. Comput..
[140] Ashish Kapoor,et al. Active learning for large multi-class problems , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.
[141] Dariu Gavrila,et al. Monocular Pedestrian Detection: Survey and Experiments , 2009, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[142] Andrew Zisserman,et al. A Statistical Approach to Material Classification Using Image Patch Exemplars , 2009, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[143] Song-Chun Zhu,et al. Learning mixed templates for object recognition , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.
[144] Tomaso Poggio,et al. Object Recognition Using Boosted Oriented Filter Based Local Descriptors , 2009 .
[145] Longin Jan Latecki,et al. Contour Grouping Based on Contour-Skeleton Duality , 2009, International Journal of Computer Vision.
[146] Horst Wildenauer,et al. Spatial Configuration of Local Shape Features for Discriminative Object Detection , 2009, ISVC.
[147] Takeo Kanade,et al. A robust shape model for multi-view car alignment , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.
[148] Charless C. Fowlkes,et al. Discriminative Models for Multi-Class Object Layout , 2009, 2009 IEEE 12th International Conference on Computer Vision.
[149] Gertjan J. Burghouts,et al. Performance evaluation of local colour invariants , 2009, Comput. Vis. Image Underst..
[150] Allan Hanbury,et al. Invariant Shape Matching for Detection of Semi-local Image Structures , 2009, ICIAR.
[151] M. Fatih Demirci,et al. Skeletal Shape Abstraction from Examples , 2009, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[152] Christoph Schnörr,et al. A Study of Parts-Based Object Class Detection Using Complete Graphs , 2010, International Journal of Computer Vision.
[153] Song-Chun Zhu,et al. Learning Active Basis Model for Object Detection and Recognition , 2010, International Journal of Computer Vision.
[154] Bruce A. Draper,et al. Interest Point Stability Prediction , 2009, ICVS.
[155] Susanto Rahardja,et al. Structural Descriptors for Category Level Object Detection , 2009, IEEE Transactions on Multimedia.
[156] Aleix M. Martínez,et al. Rotation Invariant Kernels and Their Application to Shape Analysis , 2009, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[157] Tieniu Tan,et al. Toward Accurate and Fast Iris Segmentation for Iris Biometrics , 2009, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[158] Yi Liu,et al. Learning Robust Similarity Measures for 3D Partial Shape Retrieval , 2010, International Journal of Computer Vision.
[159] Xiaoou Tang,et al. 2D Shape Matching by Contour Flexibility , 2009, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[160] Trevor Darrell,et al. Fast concurrent object localization and recognition , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.
[161] Svetlana Lazebnik,et al. Supervised Learning of Quantizer Codebooks by Information Loss Minimization , 2009, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[162] Michael Lindenbaum,et al. Optimizing Gabor Filter Design for Texture Edge Detection and Classification , 2009, International Journal of Computer Vision.
[163] Mario Fritz,et al. Discriminative structure learning of hierarchical representations for object detection , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.
[164] Reducing JointBoost-based multiclass classification to proximity search , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.
[165] Dimitris N. Metaxas,et al. D - Clutter: Building object model library from unsupervised segmentation of cluttered scenes , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.
[166] Luo Juan,et al. A comparison of SIFT, PCA-SIFT and SURF , 2009 .
[167] H. Grabner,et al. Classifier grids for robust adaptive object detection , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.
[168] Jiri Matas,et al. Learning Fast Emulators of Binary Decision Processes , 2009, International Journal of Computer Vision.
[169] Nenghai Yu,et al. Scale-Invariant Visual Language Modeling for Object Categorization , 2009, IEEE Trans. Multim..
[170] Maylor K. H. Leung,et al. An ellipse detection method for real images , 2010, 2010 25th International Conference of Image and Vision Computing New Zealand.
[171] Larry S. Davis,et al. Shape-Based Human Detection and Segmentation via Hierarchical Part-Template Matching , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[172] B. Mohan,et al. Improving the Accuracy of Object Based Supervised Image Classification using Cloud Basis Function Neural Network for High Resolution Satellite Images , 2010 .
[173] Hongzhi Wang,et al. Rigid Shape Matching by Segmentation Averaging , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[174] Andrew Zisserman,et al. OBJCUT: Efficient Segmentation Using Top-Down and Bottom-Up Cues , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[175] Maylor K. H. Leung,et al. A hybrid approach for ellipse detection in real images , 2010, International Conference on Digital Image Processing.
[176] Maylor K. H. Leung,et al. Reliability / precision uncertainity in shape fitting problems , 2010, 2010 IEEE International Conference on Image Processing.
[177] Joachim M. Buhmann,et al. Learning the Compositional Nature of Visual Object Categories for Recognition , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[178] David Gerónimo Gómez,et al. 2D-3D-based on-board pedestrian detection system , 2010, Comput. Vis. Image Underst..
[179] Dilip Kumar Prasad,et al. Error Analysis of Geometric Ellipse Detection Methods Due to Quantization , 2010, 2010 Fourth Pacific-Rim Symposium on Image and Video Technology.
[180] Jitendra Malik,et al. Shape matching and object recognition using shape contexts , 2010, 2010 3rd International Conference on Computer Science and Information Technology.
[181] Raj Kumar Gupta,et al. An Error Bounded Tangent Estimator for Digitized Elliptic Curves , 2011, DGCI.
[182] Changsheng Xu,et al. Boosting part-sense multi-feature learners toward effective object detection , 2011, Comput. Vis. Image Underst..
[183] Pietro Perona,et al. Object detection and segmentation from joint embedding of parts and pixels , 2011, 2011 International Conference on Computer Vision.
[184] Pedro F. Felzenszwalb. Object detection grammars , 2011, 2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops).
[185] Bernt Schiele,et al. Discriminative Appearance Models for Pictorial Structures , 2011, International Journal of Computer Vision.
[186] Longin Jan Latecki,et al. From partial shape matching through local deformation to robust global shape similarity for object detection , 2011, CVPR 2011.
[187] Andrew Zisserman,et al. Tabula rasa: Model transfer for object category detection , 2011, 2011 International Conference on Computer Vision.
[188] Joshua B. Tenenbaum,et al. Learning to share visual appearance for multiclass object detection , 2011, CVPR 2011.
[189] François Fleuret,et al. Tasting families of features for image classification , 2011, 2011 International Conference on Computer Vision.
[190] Huafu Chen,et al. Two-class support vector data description , 2011, Pattern Recognit..
[191] Matthew B. Blaschko,et al. Learning a category independent object detection cascade , 2011, 2011 International Conference on Computer Vision.
[192] Barbara Caputo,et al. Multiclass transfer learning from unconstrained priors , 2011, 2011 International Conference on Computer Vision.
[193] Luc Van Gool,et al. Scalable multi-class object detection , 2011, CVPR 2011.
[194] Dilip K. Prasad. Adaptive traffic signal control system with cloud computing based online learning , 2011, 2011 8th International Conference on Information, Communications & Signal Processing.
[195] Hamid R. Rabiee,et al. RASIM: A Novel Rotation and Scale Invariant Matching of Local Image Interest Points , 2011, IEEE Transactions on Image Processing.
[196] Yannis Avrithis,et al. Speeded-up, relaxed spatial matching , 2011, 2011 International Conference on Computer Vision.
[197] Wenyu Liu,et al. Feature context for image classification and object detection , 2011, CVPR 2011.
[198] Antonis A. Argyros,et al. Unsupervised learning of background modeling parameters in multicamera systems , 2011, Comput. Vis. Image Underst..
[199] Hiok Chai Quek,et al. A parameter independent line fitting method , 2011, The First Asian Conference on Pattern Recognition.
[200] Shang-Hong Lai,et al. Fusing generic objectness and visual saliency for salient object detection , 2011, 2011 International Conference on Computer Vision.
[201] Dilip K. Prasad,et al. Assessing Error Bound For Dominant Point Detection , 2012 .
[202] Nilanjan Ray,et al. Object Detection With DoG Scale-Space: A Multiple Kernel Learning Approach , 2012, IEEE Transactions on Image Processing.
[203] Dilip K. Prasad. High Availability Based Migration Analysis to Cloud Computing for High Growth Businesses , 2012 .
[204] Hiok Chai Quek,et al. A Precise Ellipse Fitting Method for Noisy Data , 2012, ICIAR.
[205] Aleix M. Martínez,et al. Learning deformable shape manifolds , 2012, Pattern Recognit..
[206] Sven J. Dickinson,et al. Discovering hierarchical object models from captioned images , 2012, Comput. Vis. Image Underst..
[207] Hiok Chai Quek,et al. A novel framework for making dominant point detection methods non-parametric , 2012, Image Vis. Comput..
[208] Dilip K. Prasad,et al. Methods for Ellipse Detection from Edge Maps of Real Images , 2012 .
[209] Dilip K. Prasad,et al. Polygonal Representation of Digital Curves , 2012 .
[210] Francesc Moreno-Noguer,et al. Bootstrapping Boosted Random Ferns for discriminative and efficient object classification , 2012, Pattern Recognit..
[211] Nicu Sebe,et al. Sparse Color Interest Points for Image Retrieval and Object Categorization , 2012, IEEE Transactions on Image Processing.
[212] Hiok Chai Quek,et al. A Non-heuristic Dominant Point Detection Based on Suppression of Break Points , 2012, ICIAR.
[213] Radu Horaud,et al. Keypoints and Local Descriptors of Scalar Functions on 2D Manifolds , 2012, International Journal of Computer Vision.
[214] Chai Quek,et al. Fast Segmentation of Sub-Cellular Organelles , 2012 .
[215] Siu-Yeung Cho,et al. Edge curvature and convexity based ellipse detection method , 2012, Pattern Recognit..
[216] Hiok Chai Quek,et al. ElliFit: An unconstrained, non-iterative, least squares based geometric Ellipse Fitting method , 2013, Pattern Recognit..