Local Features and Kernels for Classification of Texture and Object Categories: A Comprehensive Study
暂无分享,去创建一个
Cordelia Schmid | Svetlana Lazebnik | Marcin Marszalek | Jianguo Zhang | S. Lazebnik | C. Schmid | Jianguo Zhang | Marcin Marszalek
[1] Martin A. Fischler,et al. The Representation and Matching of Pictorial Structures , 1973, IEEE Transactions on Computers.
[2] B. Julesz. Textons, the elements of texture perception, and their interactions , 1981, Nature.
[3] F. S. Cohen,et al. Classification of Rotated and Scaled Textured Images Using Gaussian Markov Random Field Models , 1991, IEEE Trans. Pattern Anal. Mach. Intell..
[4] Anil K. Jain,et al. Texture classification and segmentation using multiresolution simultaneous autoregressive models , 1992, Pattern Recognit..
[5] Christos Faloutsos,et al. QBIC project: querying images by content, using color, texture, and shape , 1993, Electronic Imaging.
[6] B. S. Manjunath,et al. Texture Features for Browsing and Retrieval of Image Data , 1996, IEEE Trans. Pattern Anal. Mach. Intell..
[7] Sameer A. Nene,et al. Columbia Object Image Library (COIL100) , 1996 .
[8] Andrew McCallum,et al. A comparison of event models for naive bayes text classification , 1998, AAAI 1998.
[9] Shree K. Nayar,et al. Reflectance and texture of real-world surfaces , 1999, TOGS.
[10] Jitendra Malik,et al. Recognizing surfaces using three-dimensional textons , 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision.
[11] Andrew McCallum,et al. Using Maximum Entropy for Text Classification , 1999 .
[12] Patrick Haffner,et al. Support vector machines for histogram-based image classification , 1999, IEEE Trans. Neural Networks.
[13] Andrew E. Johnson,et al. Using Spin Images for Efficient Object Recognition in Cluttered 3D Scenes , 1999, IEEE Trans. Pattern Anal. Mach. Intell..
[14] Pietro Perona,et al. Towards automatic discovery of object categories , 2000, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662).
[15] Andrew W. Moore,et al. X-means: Extending K-means with Efficient Estimation of the Number of Clusters , 2000, ICML.
[16] Kristin J. Dana,et al. Compact representation of bidirectional texture functions , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.
[17] Dan Roth,et al. Learning a Sparse Representation for Object Detection , 2002, ECCV.
[18] Andrew Zisserman,et al. Classifying Images of Materials: Achieving Viewpoint and Illumination Independence , 2002, ECCV.
[19] Cordelia Schmid,et al. An Affine Invariant Interest Point Detector , 2002, ECCV.
[20] Bo Zhang,et al. Support vector machines for region-based image retrieval , 2003, 2003 International Conference on Multimedia and Expo. ICME '03. Proceedings (Cat. No.03TH8698).
[21] Maria Petrou,et al. Classification of textures seen from different distances and under varying illumination direction , 2003, Proceedings 2003 International Conference on Image Processing (Cat. No.03CH37429).
[22] 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..
[23] Jiahua Wu,et al. Combining gradient and albedo data for rotation invariant classification of 3D surface texture , 2003, Proceedings Ninth IEEE International Conference on Computer Vision.
[24] Pietro Perona,et al. Object class recognition by unsupervised scale-invariant learning , 2003, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings..
[25] Andrew Zisserman,et al. Video Google: a text retrieval approach to object matching in videos , 2003, Proceedings Ninth IEEE International Conference on Computer Vision.
[26] Andrew Zisserman,et al. Texture classification: are filter banks necessary? , 2003, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings..
[27] Anthony Widjaja,et al. Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond , 2003, IEEE Transactions on Neural Networks.
[28] Barbara Caputo,et al. Recognition with local features: the kernel recipe , 2003, Proceedings Ninth IEEE International Conference on Computer Vision.
[29] Peter Auer,et al. Weak Hypotheses and Boosting for Generic Object Detection and Recognition , 2004, ECCV.
[30] Jitendra Malik,et al. Spectral grouping using the Nystrom method , 2004, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[31] Barbara Caputo,et al. Cue integration through discriminative accumulation , 2004, Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004..
[32] Cordelia Schmid,et al. Semi-Local Affine Parts for Object Recognition , 2004, BMVC.
[33] Barbara Caputo,et al. Object categorization via local kernels , 2004, Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004..
[34] Cordelia Schmid,et al. Scale & Affine Invariant Interest Point Detectors , 2004, International Journal of Computer Vision.
[35] David G. Lowe,et al. Distinctive Image Features from Scale-Invariant Keypoints , 2004, International Journal of Computer Vision.
[36] Mario Fritz,et al. On the Significance of Real-World Conditions for Material Classification , 2004, ECCV.
[37] 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.
[38] Tony Lindeberg,et al. Feature Detection with Automatic Scale Selection , 1998, International Journal of Computer Vision.
[39] J Eichhorn,et al. Object categorization with SVM: kernels for local features , 2004 .
[40] Gabriela Csurka,et al. Visual categorization with bags of keypoints , 2002, eccv 2004.
[41] Bernt Schiele,et al. Recognition without Correspondence using Multidimensional Receptive Field Histograms , 2004, International Journal of Computer Vision.
[42] Tony Lindeberg,et al. Direct computation of shape cues using scale-adapted spatial derivative operators , 1996, International Journal of Computer Vision.
[43] Daniel P. Huttenlocher,et al. Pictorial Structures for Object Recognition , 2004, International Journal of Computer Vision.
[44] Leonidas J. Guibas,et al. The Earth Mover's Distance as a Metric for Image Retrieval , 2000, International Journal of Computer Vision.
[45] Lixin Fan,et al. Categorizing Nine Visual Classes using Local Appearance Descriptors , 2004 .
[46] 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).
[47] S. Lazebnik,et al. Local Features and Kernels for Classification of Texture and Object Categories: An In-Depth Study , 2005 .
[48] Hermann Ney,et al. Improving a Discriminative Approach to Object Recognition Using Image Patches , 2005, DAGM-Symposium.
[49] Trevor Darrell,et al. The pyramid match kernel: discriminative classification with sets of image features , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.
[50] Cordelia Schmid,et al. A performance evaluation of local descriptors , 2005, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[51] Cordelia Schmid,et al. A sparse texture representation using local affine regions , 2005, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[52] Pietro Perona,et al. A Bayesian hierarchical model for learning natural scene categories , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).
[53] Frédéric Jurie,et al. Creating efficient codebooks for visual recognition , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.
[54] Hermann Ney,et al. Discriminative training for object recognition using image patches , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).
[55] Alexei A. Efros,et al. Discovering objects and their location in images , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.
[56] Luc Van Gool,et al. Modeling scenes with local descriptors and latent aspects , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.
[57] Siwei Lyu,et al. Mercer kernels for object recognition with local features , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).
[58] Trevor Darrell,et al. Efficient image matching with distributions of local invariant features , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).
[59] Cordelia Schmid,et al. The 2005 PASCAL Visual Object Classes Challenge , 2005, MLCW.
[60] C. Schmid,et al. Object Class Recognition Using Discriminative Local Features , 2005 .
[61] Diane Larlus,et al. Création de Vocabulaires Visuels Efficaces pour la Catégorisation d'Images , 2006 .
[62] 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).
[63] Trevor Darrell,et al. Pyramid Match Kernels: Discriminative Classification with Sets of Image Features (version 2) , 2006 .