The DOI matches its Crossref record; 53 of the 53 references it cites were found in a registry or an index.
Partial Face Recognition: Alignment-Free Approach
Abstract
Numerous methods have been developed for holistic face recognition with impressive performance. However, few studies have tackled how to recognize an arbitrary patch of a face image. Partial faces frequently appear in unconstrained scenarios, with images captured by surveillance cameras or handheld devices (e.g., mobile phones) in particular. In this paper, we propose a general partial face recognition approach that does not require face alignment by eye coordinates or any other fiducial points. We develop an alignment-free face representation method based on Multi-Keypoint Descriptors (MKD), where the descriptor size of a face is determined by the actual content of the image. In this way, any probe face image, holistic or partial, can be sparsely represented by a large dictionary of gallery descriptors. A new keypoint descriptor called Gabor Ternary Pattern (GTP) is also developed for robust and discriminative face recognition. Experimental results are reported on four public domain face databases (FRGCv2.0, AR, LFW, and PubFig) under both the open-set identification and verification scenarios. Comparisons with two leading commercial face recognition SDKs (PittPatt and FaceVACS) and two baseline algorithms (PCA+LDA and LBP) show that the proposed method, overall, is superior in recognizing both holistic and partial faces without requiring alignment.
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Cites
Distinctive Image Features from Scale-Invariant Keypoints
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A Computational Approach to Edge Detection
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Robust Face Recognition via Sparse Representation
Wright, J., Yang, A. Y., Ganesh, A., Sastry, S. S., & Ma, Y. (2009) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2008.79 · Cited by 9,388
Active Shape Models-Their Training and Application
Cootes, T. F., Taylor, C. J., Cooper, D. H., & Graham, J. (1995) · Computer Vision and Image Understanding · doi:10.1006/cviu.1995.1004 · Cited by 7,190
Stable signal recovery from incomplete and inaccurate measurements
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Face Description with Local Binary Patterns: Application to Face Recognition
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Labeled Faces in the Wild: A Database forStudying Face Recognition in Unconstrained Environments
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Visual categorization with bags of keypoints
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Cited by
Region Attention Networks for Pose and Occlusion Robust Facial Expression Recognition
Wang, K., Peng, X., Yang, J., Meng, D., & Qiao, Y. (2020) · IEEE Transactions on Image Processing · doi:10.1109/tip.2019.2956143 · Cited by 940
Face Recognition Systems: A Survey
Kortli, Y., Jridi, M., Al Falou, A., & Atri, M. (2020) · Sensors · doi:10.3390/s20020342 · Cited by 623
Deep Spatial Feature Reconstruction for Partial Person Re-identification: Alignment-free Approach
He, L., Liang, J., Li, H., & Sun, Z. (2018) · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2018.00739 · Cited by 341
Metadata
- Authors
- Liao, S., Jain, A. K., & Li, S. Z.
- Venue
- IEEE Transactions on Pattern Analysis and Machine Intelligence
- Published
- 2013-05
- Volume
- 35
- Issue
- 5
- Pages
- 1193-1205
- ISSN
- 0162-8828 (ISSN-L)
- 2160-9292
- OpenAlex
- W2099474347
- Cited by
- 313
- References
- 53
- FWCI
- 28.52
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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