Chromatic Cues for Face Detection in Natural Scenes

One of the challenging problems of human and machine vision is the detection of objects against complex backgrounds. Our research addresses the question of how faces can be very quickly detected in naturalistic scenes on the basis of luminance and chromatic cues. Although luminance information varies with pose and illumination differences, chromatic information is by and large invariant under these transformations. Hence, chromatic information might be a very powerful cue for segmentation and detection.

We compared faces of different pigmentation against background scenes of different colours. Specifically, colour histograms were computed in a perceptually uniform colour space (L*u*v*). We computed the Euclidian distances between the averages of the colour histograms of faces and scenes in L*u*v*. This metric was used to calibrate the contrast between face and scene colour in the experimental design. In a face detection task, subjects saw faces against scene backgrounds at a different distance in colour space. Each combination face - scene was presented for 120 ms (to prevent saccadic explorations), and the subject's task was to indicate whether or not a face was present. Controls involved face - scene pairs on an isoluminant background. Results revealed that luminance information did not affect detection on the basis of chromatic cues. Importantly, the metric of detectability in L*u*v* space between scene and faces predicted reaction times to detection.