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

Elephants can determine ethnicity, gender, and age from acoustic cues in human voices

Animals can accrue direct fitness benefits by accurately classifying predatory threat according to the species of predator and the magnitude of risk associated with an encounter. Human predators present a particularly interesting cognitive challenge, as it is typically the case that different human subgroups pose radically different levels of danger to animals living around them. Although a number of prey species have proved able to discriminate between certain human categories on the basis of visual and olfactory cues, vocalizations potentially provide a much richer source of information. We now use controlled playback experiments to investigate whether family groups of free-ranging African elephants (Loxodonta africana) in Amboseli National Park, Kenya can use acoustic characteristics of speech to make functionally relevant distinctions between human subcategories differing not only in ethnicity but also in sex and age. Our results demonstrate that elephants can reliably discriminate between two different ethnic groups that differ in the level of threat they represent, significantly increasing their probability of defensive bunching and investigative smelling following playbacks of Maasai voices. Moreover, these responses were specific to the sex and age of Maasai presented, with the voices of Maasai women and boys, subcategories that would generally pose little threat, significantly less likely to produce these behavioral responses. Considering the long history and often pervasive predatory threat associated with humans across the globe, it is likely that abilities to precisely identify dangerous subcategories of humans on the basis of subtle voice characteristics could have been selected for in other cognitively advanced animal species

Emphatic agents to reduce user frustration: The effects of varying agent characteristics

There is now growing interest in the development of computer systems which respond to users’ emotion and affect. We report three small scale studies (with a total of 42 participants) which investigate the extent to which affective agents, using strategies derived from human-human interaction, can reduce user frustration within human-computer interaction. The results confirm the previous findings of Klein et al (2002) that such interventions can be effective. We also obtained results that suggest that embodied agents can be more effective at reducing frustration than non-embodied agents, and that female embodied agents may be more effective than male embodied agents. These results are discussed in light of the existing research literature