The DOI matches its Crossref record; 28 of the 28 references it cites were found in a registry or an index.
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
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- everingham, 0, The PASCAL Visual Object Classes Challenge 2007 (VOC2007) Results
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A CNN-based multi-task framework for weather recognition with multi-scale weather cues
Xie, K., Huang, L., Zhang, W., Qin, Q., & Lyu, L. (2022) · Expert Systems with Applications · doi:10.1016/j.eswa.2022.116689 · Cited by 24
A group lasso based sparse KNN classifier
Zheng, S., & Ding, C. (2020) · Pattern Recognition Letters · doi:10.1016/j.patrec.2019.12.020 · Cited by 22
Automatic placental maturity grading via hybrid learning
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Metadata
- 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
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