Proceedings ArticleDOI
On rank aggregation for face recognition from videos
Himanshu Bhatt,Richa Singh,Mayank Vatsa +2 more
- pp 2993-2997
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TLDR
A video based face recognition algorithm that computes a discriminative video signature as an ordered list of still face images to facilitate matching two videos with large variations is presented.Abstract:
Face recognition from still face images suffers due to intrapersonal variations caused by pose, illumination, and expression that degrade the performance. On the other hand, videos provide abundant information that can be leveraged to compensate the limitations of still face images and enhance face recognition performance. This paper presents a video based face recognition algorithm that computes a discriminative video signature as an ordered list of still face images. The video signature embeds diverse intra-personal and temporal variations across multiple frames, thus facilitates matching two videos with large variations. Two videos are matched by comparing their discriminative signatures using the Kendall tau similarity distance measure. Performance comparison with the benchmark results and a commercial face recognition system on the publicly available YouTube faces database show the efficacy of the proposed video based face recognition algorithm.read more
Citations
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Journal ArticleDOI
On Recognizing Faces in Videos Using Clustering-Based Re-Ranking and Fusion
TL;DR: A video-based face recognition algorithm that computes a discriminative video signature as an ordered list of still face images from a large dictionary, which embeds diverse intra-personal variations and facilitates in matching two videos with large variations.
Proceedings ArticleDOI
Video-to-video face matching: Establishing a baseline for unconstrained face recognition
TL;DR: This work demonstrates that all three COTS matchers individually are superior to previously published face recognition results on the unconstrained YouTube Faces database and achieves a 20% improvement in accuracy over previously published results.
Proceedings ArticleDOI
On video based face recognition through adaptive sparse dictionary
TL;DR: This paper proposes a video-based face recognition method which improves upon the sparse representation framework with an intelligent and adaptive sparse dictionary that updates the current probe image into the training matrix based on continuously monitoring the probe video through a novel confidence criterion and a Bayesian inference scheme.
Patent
System for video based face recognition using an adaptive dictionary
TL;DR: In this paper, a dictionary including a target collection defined by images that are known with a defined level of certainty to include a subject and an imposter collection defined of images of individuals other than the subject is used.
Proceedings ArticleDOI
An approach to improvise recognition rate from occluded and pose variant faces
A. Vijayalakshmi,Pethuru Raj +1 more
TL;DR: A model that can increase the recognition rate with faces of different pose and faces subjected to occlusion is proposed and the technique of in-painting to restore the occluded face in a frame of video is introduced.
References
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BookDOI
Handbook of Face Recognition
Stan Z. Li,Anil K. Jain +1 more
TL;DR: This highly anticipated new edition provides a comprehensive account of face recognition research and technology, spanning the full range of topics needed for designing operational face recognition systems, as well as offering challenges and future directions.
Proceedings ArticleDOI
Face recognition in unconstrained videos with matched background similarity
Lior Wolf,Tal Hassner,Itay Maoz +2 more
TL;DR: A comprehensive database of labeled videos of faces in challenging, uncontrolled conditions, the ‘YouTube Faces’ database, along with benchmark, pair-matching tests are presented and a novel set-to-set similarity measure, the Matched Background Similarity (MBGS), is described.