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Detecting Faces in Impoverished Images

dc.date.accessioned2004-10-20T21:03:55Z
dc.date.accessioned2018-11-24T10:23:29Z
dc.date.available2004-10-20T21:03:55Z
dc.date.available2018-11-24T10:23:29Z
dc.date.issued2001-11-05en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/7242
dc.identifier.urihttp://repository.aust.edu.ng/xmlui/handle/1721.1/7242
dc.description.abstractThe ability to detect faces in images is of critical ecological significance. It is a pre-requisite for other important face perception tasks such as person identification, gender classification and affect analysis. Here we address the question of how the visual system classifies images into face and non-face patterns. We focus on face detection in impoverished images, which allow us to explore information thresholds required for different levels of performance. Our experimental results provide lower bounds on image resolution needed for reliable discrimination between face and non-face patterns and help characterize the nature of facial representations used by the visual system under degraded viewing conditions. Specifically, they enable an evaluation of the contribution of luminance contrast, image orientation and local context on face-detection performance.en_US
dc.format.extent14 p.en_US
dc.format.extent20987363 bytes
dc.format.extent1810477 bytes
dc.language.isoen_US
dc.subjectAIen_US
dc.subjectFace detectionen_US
dc.subjectimage resolutionen_US
dc.subjectcontrast negationen_US
dc.subjectvertical inversionen_US
dc.titleDetecting Faces in Impoverished Imagesen_US


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