Locality-constrained Linear Coding for image classification
Abstract
The traditional SPM approach based on bag-of-features (BoF) requires nonlinear classifiers to achieve good image classification performance. This paper presents a simple but effective coding scheme called Locality-constrained Linear Coding (LLC) in place of the VQ coding in traditional SPM. LLC utilizes the locality constraints to project each descriptor into its local-coordinate system, and the projected coordinates are integrated by max pooling to generate the final representation. With linear classifier, the proposed approach performs remarkably better than the traditional nonlinear SPM, achieving state-of-the-art performance on several benchmarks. Compared with the sparse coding strategy [22], the objective function used by LLC has an analytical solution. In addition, the paper proposes a fast approximated LLC method by first performing a K-nearest-neighbor search and then solving a constrained least square fitting problem, bearing computational complexity of O(M + K2). Hence even with very large codebooks, our system can still process multiple frames per second. This efficiency significantly adds to the practical values of LLC for real applications.
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Histograms of Oriented Gradients for Human Detection
Dalal, N., & Triggs, B. (2005) · 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) · doi:10.1109/cvpr.2005.177 · Cited by 33,584 · see citing works
Nonlinear Dimensionality Reduction by Locally Linear Embedding
Roweis, S. T., & Saul, L. K. (2000) · Science · doi:10.1126/science.290.5500.2323 · Cited by 14,965 · see citing works
Beyond Bags of Features: Spatial Pyramid Matching for Recognizing Natural Scene Categories
Lazebnik, S., Schmid, C., & Ponce, J. (2006) · 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2 (CVPR'06) · doi:10.1109/cvpr.2006.68 · Cited by 7,916 · see citing works
Video Google: a text retrieval approach to object matching in videos
Sivic, & Zisserman (2003) · Proceedings Ninth IEEE International Conference on Computer Vision · doi:10.1109/iccv.2003.1238663 · Cited by 6,367 · see citing works
Visual categorization with bags of keypoints
Csurka, G. (2004) · Cited by 4,379 · see citing works
Linear spatial pyramid matching using sparse coding for image classification
Yang, J., Yu, K., Gong, Y., & Huang, T. S. (2009) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2009.5206757 · Cited by 2,895 · see citing works
Self-citationEfficient sparse coding algorithms
Lee, H., Battle, A. J., Raina, R., & Ng, A. Y. (2007) · The MIT Press eBooks · doi:10.7551/mitpress/7503.003.0105 · Cited by 2,449 · see citing works
Fei-Fei, L., Fergus, R., & Perona, P. (2007) · Computer Vision and Image Understanding · doi:10.1016/j.cviu.2005.09.012 · Cited by 2,359 · see citing works
(2007) · CaltechAUTHORS (California Institute of Technology) · Cited by 2,274 · see citing works
The PASCAL visual object classes challenge 2006 (VOC2006) results
Everingham, M., Zisserman, A., Williams, C. K. I., & Gool, L. V. (2006) · Cited by 2,079 · see citing works
The pyramid match kernel: discriminative classification with sets of image features
Grauman, K. L., & Darrell, T. (2005) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2005.239 · Cited by 1,500 · see citing works
SVM-KNN: Discriminative Nearest Neighbor Classification for Visual Category Recognition
Zhang, H., Berg, A. C., Maire, M., & Malik, J. (2006) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2006.301 · Cited by 1,128 · see citing works
In defense of Nearest-Neighbor based image classification
Boiman, O., Shechtman, E., & Irani, M. (2008) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2008.4587598 · Cited by 1,079 · see citing works
A numerically stable dual method for solving strictly convex quadratic programs
Goldfarb, D., & Idnani, A. (1983) · Mathematical Programming · doi:10.1007/bf02591962 · Cited by 1,067 · see citing works
Shape Matching and Object Recognition Using Low Distortion Correspondences
Berg, A. C., Berg, T. L., & Malik, J. (2005) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2005.320 · Cited by 850 · see citing works
Creating efficient codebooks for visual recognition
Jurie, F., & Triggs, B. (2005) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2005.66 · Cited by 713 · see citing works
Scene Classification Using a Hybrid Generative/Discriminative Approach
Bosch, A., Zisserman, A., & Muñoz, X. (2008) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2007.70716 · Cited by 682 · see citing works
Nonlinear Learning using Local Coordinate Coding
Yu, K., Zhang, T., & Gong, Y. (2009) · Cited by 681 · see citing works
Self-citationKernel Codebooks for Scene Categorization
van Gemert, J. C., Geusebroek, J., Veenman, C. J., & Smeulders, A. W. M. (2008) · Lecture notes in computer science · doi:10.1007/978-3-540-88690-7_52 · Cited by 591 · see citing works
Linear spatial pyramid matching using sparse coding for image classification
Yang, J., Yu, K., Gong, Y., & Huang, T. S. (2009) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvprw.2009.5206757 · Cited by 496 · see citing works
Self-citationFast image search for learned metrics
Jain, P., Kulis, B., & Grauman, K. L. (2008) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2008.4587841 · Cited by 280 · see citing works
Visual categorization with bags of keypoints
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Liu, Y., Jin, R., Sukthankar, R., & Jurie, F. (2008) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2008.4587504 · Cited by 241 · see citing works
A maximum entropy framework for part-based texture and object recognition
Lazebnik, S., Schmid, C., & Ponce, J. (2005) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2005.10 · Cited by 192 · see citing works
Hierarchical Gaussianization for image classification
Zhou, X., Cui, N., Li, Z., Liang, F., & Huang, T. S. (2009) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2009.5459435 · Cited by 148 · see citing works
Self-citationResolution enhancement based on learning the sparse association of image patches
Wang, J., Zhu, S., & Gong, Y. (2009) · Pattern Recognition Letters · doi:10.1016/j.patrec.2009.09.004 · Cited by 85 · see citing works
Self-citationWhat is the spatial extent of an object?
Uijlings, J., Smeulders, A. W. M., & Scha, R. J. H. (2009) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2009.5206663 · Cited by 52 · see citing works
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He, K., Zhang, X., Ren, S., & Sun, J. (2015) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2015.2389824 · Cited by 11,971 · see citing works
On Pixel-Wise Explanations for Non-Linear Classifier Decisions by Layer-Wise Relevance Propagation
Bach, S., Binder, A., Montavon, G., Klauschen, F., Müller, K.-R., & Samek, W. (2015) · PLOS ONE · doi:10.1371/journal.pone.0130140 · Cited by 4,524 · see citing works
DeCAF: A Deep Convolutional Activation Feature for Generic Visual Recognition
Donahue, J., Jia, Y., Vinyals, O., Hoffman, J., Zhang, N., Tzeng, E., & Darrell, T. (2013) · arXiv · doi:10.48550/arxiv.1310.1531 · Cited by 4,019 · see citing works
3D Object Representations for Fine-Grained Categorization
Krause, J., Stark, M. M., Deng, J., & Fei-Fei, L. (2013) · IEEE International Conference on Computer Vision Workshops · doi:10.1109/iccvw.2013.77 · Cited by 3,523 · see citing works
Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition
He, K., Zhang, X., Ren, S., & Sun, J. (2014) · Lecture Notes in Computer Science · doi:10.1007/978-3-319-10578-9_23 · Cited by 3,034 · see citing works
Remote Sensing Image Scene Classification: Benchmark and State of the Art
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YOLACT: Real-Time Instance Segmentation
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Deep learning for visual understanding: A review
Guo, Y., Liu, Y., Oerlemans, A., Lao, S., Wu, S., & Lew, M. S. (2016) · Neurocomputing · doi:10.1016/j.neucom.2015.09.116 · Cited by 2,504 · see citing works
Describing Textures in the Wild
Cimpoi, M., Maji, S., Kokkinos, I., Mohamed, S., & Vedaldi, A. (2014) · 2014 IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2014.461 · Cited by 2,438 · see citing works
AID: A Benchmark Data Set for Performance Evaluation of Aerial Scene Classification
Xia, G.-S., Hu, J., Hu, F., Shi, B., Bai, X., Zhong, Y., Zhang, L., & Lu, X. (2017) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2017.2685945 · Cited by 2,423 · see citing works
Deep Learning for Remote Sensing Data: A Technical Tutorial on the State of the Art
Zhang, L., Zhang, L., & Du, B. (2016) · IEEE Geoscience and Remote Sensing Magazine · doi:10.1109/mgrs.2016.2540798 · Cited by 2,229 · see citing works
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Hu, F., Xia, G.-S., Hu, J., & Zhang, L. (2015) · Remote Sensing · doi:10.3390/rs71114680 · Cited by 1,199 · see citing works
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Self-citationMulti-scale Orderless Pooling of Deep Convolutional Activation Features
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Cheng, J., Huang, W., Cao, S., Yang, R., Yang, W., Yun, Z., Wang, Z., & Feng, Q. (2015) · PLOS ONE · doi:10.1371/journal.pone.0140381 · Cited by 879 · see citing works
“Other more sophisticated methods may also be used, such as SC, soft assignment (SA) [24,25], orthogonal matching pursuit (OMP), locality-constrained linear coding [26], and local anchor embedding [27].”
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Unsupervised feature learning framework for no-reference image quality assessment
Ye, P., Kumar, J., Kang, L., & Doermann, D. S. (2012) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2012.6247789 · Cited by 833 · see citing works
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Xie, L., & Yuille, A. (2017) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2017.154 · Cited by 904 · see citing works
Han, J., Zhang, D., Cheng, G., Guo, L., & Ren, J. (2014) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2014.2374218 · Cited by 734 · see citing works
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Cimpoi, M., Maji, S., & Vedaldi, A. (2015) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2015.7299007 · Cited by 670 · see citing works
Human action recognition by learning bases of action attributes and parts
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Thompson, N. C., Greenewald, K., Lee, K., & Manso, G. F. (2020) · arXiv · doi:10.48550/arxiv.2007.05558 · Cited by 538 · see citing works
(2011) · Cited by 514 · see citing works
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The intrinsic memorability of face photographs.
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Zou, Q., Zeng, J., Cao, L., & Ji, R. (2015) · Neurocomputing · doi:10.1016/j.neucom.2014.12.123 · Cited by 396 · see citing works
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Andreopoulos, A., & Tsotsos, J. K. (2013) · Computer Vision and Image Understanding · doi:10.1016/j.cviu.2013.04.005 · Cited by 347 · see citing works
Deep Filter Banks for Texture Recognition, Description, and Segmentation
Cimpoi, M., Maji, S., Kokkinos, I., & Vedaldi, A. (2016) · International Journal of Computer Vision · doi:10.1007/s11263-015-0872-3 · Cited by 340 · see citing works
Sparse Modeling for Image and Vision Processing
Mairal, J. (2014) · now publishers, Inc. eBooks · doi:10.1561/9781680830095 · Cited by 332 · see citing works
Auto-Encoders in Deep Learning—A Review with New Perspectives
Chen, S., & Guo, W. (2023) · Mathematics · doi:10.3390/math11081777 · Cited by 341 · see citing works
Partial Person Re-Identification
Zheng, W., Xiang, L., Xiang, T., Liao, S., Lai, J., & Gong, S. (2015) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2015.531 · Cited by 321 · see citing works
Depth kernel descriptors for object recognition
Bo, L., Ren, X., & Fox, D. (2011) · IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros.2011.6095119 · Cited by 317 · see citing works
Sparse Modeling for Image and Vision Processing
Ponce, J., Mairal, J., Bach, F., Image, S. M., Processing, V., Hal, H. I., & Supérieure, E. N. (2014) · Cited by 313 · see citing works
Evaluating knowledge transfer and zero-shot learning in a large-scale setting
Rohrbach, M., Stark, M. M., & Schiele, B. (2011) · doi:10.1109/cvpr.2011.5995627 · Cited by 309 · see citing works
Robust Object Tracking via Sparse Collaborative Appearance Model
Zhong, W., Lu, H., & Yang, M. (2014) · IEEE Transactions on Image Processing · doi:10.1109/tip.2014.2313227 · Cited by 309 · see citing works
A Probabilistic Collaborative Representation Based Approach for Pattern Classification
Cai, S., Lei Zhang, A., Zuo, W., & Feng, X. (2016) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2016.322 · Cited by 304 · see citing works
Refining activation downsampling with SoftPool
Stergiou, A., Poppe, R. W., & Kalliatakis, G. (2021) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv48922.2021.01019 · Cited by 306 · see citing works
Learning Discriminative Reconstructions for Unsupervised Outlier Removal
Xia, Y., Cao, X., Wen, F., Hua, G., & Sun, J. Z. (2015) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2015.177 · Cited by 297 · see citing works
Li, E., Xia, J., Du, P., Lin, C., & Samat, A. (2017) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2017.2711275 · Cited by 296 · see citing works
Kernel Descriptors for Visual Recognition
Bo, L., Ren, X., & Fox, D. (2010) · Cited by 290 · see citing works
Deeply learned attributes for crowded scene understanding
Shao, J., Kang, K., Loy, C. C., & Wang, X. (2015) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2015.7299097 · Cited by 291 · see citing works
Large-Scale Video Summarization Using Web-Image Priors
Khosla, A., Hamid, R., Lin, C., & Sundaresan, N. (2013) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2013.348 · Cited by 292 · see citing works
Combining randomization and discrimination for fine-grained image categorization
Yao, B., Khosla, A., & Fei-Fei, L. (2011) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2011.5995368 · Cited by 291 · see citing works
Learning Structured Low-Rank Representations for Image Classification
Zhang, Y., Jiang, Z., & Davis, L. S. (2013) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2013.93 · Cited by 283 · see citing works
An Efficient Method for Traffic Sign Recognition Based on Extreme Learning Machine
Huang, Z., Yu, Y., Gu, J. J., & Liu, H. (2016) · IEEE Transactions on Cybernetics · doi:10.1109/tcyb.2016.2533424 · Cited by 281 · see citing works
Ask the locals: Multi-way local pooling for image recognition
Boureau, Y.-L., Roux, N. L., Bach, F., Ponce, J., & LeCun, Y. (2011) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2011.6126555 · Cited by 279 · see citing works
Automatic Expansion of a Food Image Dataset Leveraging Existing Categories with Domain Adaptation
Kawano, Y., & Yanai, . (2015) · Lecture notes in computer science · doi:10.1007/978-3-319-16199-0_1 · Cited by 276 · see citing works
High-dimensional signature compression for large-scale image classification
Sanchez, J., & Perronnin, F. (2011) · CVPR 2011 · doi:10.1109/cvpr.2011.5995504 · Cited by 272 · see citing works
Efficient and accurate approximations of nonlinear convolutional networks
Zhang, X., Zou, J., Xiang, M., He, K., & Sun, J. (2015) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2015.7298809 · Cited by 267 · see citing works
- Authors
- Wang, J., Yang, J., Yu, K., Lv, F., Huang, T., & Gong, Y.
- Affiliations
- University of Illinois Urbana-Champaign (US)
- NEC (United States) (US)
- Venue
- 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition
- Publisher
- IEEE
- Published
- 2010-06
- Pages
- 3360-3367
- ISSN
- 1063-6919 (ISSN-L)
- OpenAlex
- W2027922120
- Semantic Scholar
- 2f7713dcc35e7c05becf3be5522f36c9546b0364
- Cited by
- 3,100
- References
- 28
- Citations by year
- 2026: 10 · 2025: 24 · 2024: 42 · 2023: 51 · 2022: 66 · 2021: 100 · 2020: 124 · 2019: 198 · 2018: 275 · 2017: 336 · 2016: 420 · 2015: 473 · 2014: 417 · 2013: 296 · 2012: 176
- FWCI
- 154.25
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Image and Video Retrieval Techniques
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Image Retrieval and Classification Techniques
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Neural Network Applications
- Keywords
- locality-constrained linear coding, bag of visual words, image classification, local coordinate system, max pooling, linear classifiers, k-nearest neighbor search, constrained least squares, real-time processing
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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