Face Recognition Under Varying Illumination Using Gradientfaces
By Taiping Zhang, Yuanyan Tang, Bin Fang, Zhaowei Shang, Xiaoyu Liu. IEEE Transactions on Image Processing, 2009
427 citations recorded by the source corpus.
Subfields: Computer Vision and Pattern Recognition
View Paper: https://www.semanticscholar.org/paper/ad7b6d2e8d66f720cc83323a0700c25006d49609
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computer Vision and Pattern Recognition
- Guoying Zhao
- Dacheng Tao
- Luc Van Gool
- Xiaopeng Hong
- Xiaogang Wang
- Ramalingam Chellappa
- Yi Yang
- Zhengjun Zha
Citations in the corpus
- Towards Reading Hidden Emotions: A Comparative Study of Spontaneous Micro-Expression Spotting and Recognition Methods (2015, background): “does not depend on the illuminance at pixel x [54].”
- Local Directional Number Pattern for Face Analysis: Face and Expression Recognition (2013, methodology): “Given that SVM makes binary decisions, multi-class clas-sification can be achieved by adopting the one-against-one or one-against-all techniques.”
- Adaptive Transfer Network for Cross-Domain Person Re-Identification (2019, background): “where H(·) denotes abstracting illumination insensitive features [39].”
- Face Recognition Across Non-Uniform Motion Blur, Illumination, and Pose (2015, methodology): “For handling illumination, there have mainly been two directions of pursuit based on (i) the nine-dimensional subspace model for face [20] and (ii) extracting and matching illumination insensitive facial features [21], [22].”