Machine Analysis of Facial Expressions

No abstract

"'Who are you?' - Learning person specific classifiers from video"

We investigate the problem of automatically labelling faces of characters in TV or movie material with their names, using only weak supervision from automaticallyaligned subtitle and script text. Our previous work (Everingham et al. [8]) demonstrated promising results on the task, but the coverage of the method (proportion of video labelled) and generalization was limited by a restriction to frontal faces and nearest neighbour classification. In this paper we build on that method, extending the coverage greatly by the detection and recognition of characters in profile views. In addition, we make the following contributions: (i) seamless tracking, integration and recognition of profile and frontal detections, and (ii) a character specific multiple kernel classifier which is able to learn the features best able to discriminate between the characters. We report results on seven episodes of the TV series “Buffy the Vampire Slayer”, demonstrating significantly increased coverage and performance with respect to previous methods on this material

Infrared face recognition: a comprehensive review of methodologies and databases

Automatic face recognition is an area with immense practical potential which includes a wide range of commercial and law enforcement applications. Hence it is unsurprising that it continues to be one of the most active research areas of computer vision. Even after over three decades of intense research, the state-of-the-art in face recognition continues to improve, benefitting from advances in a range of different research fields such as image processing, pattern recognition, computer graphics, and physiology. Systems based on visible spectrum images, the most researched face recognition modality, have reached a significant level of maturity with some practical success. However, they continue to face challenges in the presence of illumination, pose and expression changes, as well as facial disguises, all of which can significantly decrease recognition accuracy. Amongst various approaches which have been proposed in an attempt to overcome these limitations, the use of infrared (IR) imaging has emerged as a particularly promising research direction. This paper presents a comprehensive and timely review of the literature on this subject. Our key contributions are: (i) a summary of the inherent properties of infrared imaging which makes this modality promising in the context of face recognition, (ii) a systematic review of the most influential approaches, with a focus on emerging common trends as well as key differences between alternative methodologies, (iii) a description of the main databases of infrared facial images available to the researcher, and lastly (iv) a discussion of the most promising avenues for future research.Comment: Pattern Recognition, 2014. arXiv admin note: substantial text overlap with arXiv:1306.160