Face image quality assessment based on learning to rank
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The document discusses the significance of face image quality in automatic face recognition systems. It introduces a learning to rank based framework for assessing face image quality, which aims to select high-quality images to enhance system performance. Experimental results indicate that this method effectively improves the robustness of face detection and recognition.
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Face image quality assessment based on learning to rank
- 1. FACE IMAGE QUALITY ASSESSMENT BASED ON LEARNING TO RANK ABSTRACT Face image quality is an important factor affecting the accuracy of automatic face recognition. It is usually possible for practical recognition systems to capture multiple face images from each subject. Selecting face images with high quality for recognition is a promising stratagem for improving the system performance. We propose a learning to rank based framework for assessing the face image quality. The proposed method is simple and can adapt to different recognition methods. Experimental result demonstrates its effectiveness in improving the robustness of face detection and recognition.