Diego A. Socolinsky

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We present a comprehensive performance analysis of multiple appearance-based face recognition methodologies, on visible and thermal infrared imagery. We compare algorithms within and between modalities in terms of recognition performance, false alarm rates and requirements to achieve specified performance levels. The effect of illumination conditions on(More)
We present a new formalism for the treatment and understanding of multispectral images and multisensor imagery based on first-order contrast information. Although little attention has been paid to the utility of multispectral contrast, we develop a theory for multispectral contrast that enables us to produce an optimal grayscale visualization of the(More)
A key problem for face recognition has been accurate identification under variable illumination conditions. Conventional video cameras sense reflected light so that image grayvalues are a product of both intrinsic skin reflectivity and external incident illumination, thus obfuscating the intrinsic reflectivity of skin. Thermal emission from skin, on the(More)
We present results on the latest advances in thermal infrared face recognition, and its use in combination with visible imagery. Previous research by the authors has shown high performance under very controlled conditions, or questionable performance under a wider range of conditions. This paper shows results on the use of thermal infrared and visible(More)
Previous research has established thermal infrared imagery of faces as a valid biometric and has shown high recognition performance in a wide range of scenarios. However, all these results have been obtained using eye locations that were either manually marked, or automatically detected in a coregistered visible image, making the realistic use of thermal(More)
Detecting and tracking face regions in image sequences has applications to important problems such as face recognition, human-computer interaction, and video surveillance. Visible sensors have inherent limitations in solving this task, such as the need for sufficient and specific lighting conditions, as well as sensitivity to variations in skin color.(More)
We present a comparative study of face recognition performance with visible and thermal infrared imagery, emphasizing the influence of time-lapse between enrollment and testing images. Most previous research in this area, with few exceptions, focused on results obtained when enrollment and testing images were acquired in the same session. We show that the(More)