Acquisition of high-resolution images through on-line saccade sequence planning
Proceedings of the third ACM international workshop on Video surveillance & sensor networks
Towards on-line saccade planning for high-resolution image sensing
Pattern Recognition Letters
Towards on-line saccade planning for high-resolution image sensing
Pattern Recognition Letters - Special issue on vision for crime detection and prevention
Content and task-based view selection from multiple video streams
Multimedia Tools and Applications
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Conventional surveillance sensors suffer from an unaviodable tradeoff between image resolution and field of view. This problem may be overcome by combining a fixed, preattentive, low-resolution wide-field camera with a shiftable, attentive, high-resolution narrow-field camera.Here we present techniques for orienting the attentive camera to faces detected in the pre-attentive wide-field image stream.' Unfortunately, the low image resolution of the wide-field sensor precludes the use of most conventional face-detection algorithms.Instead, we argue that reliable performance can best be achieved by accurate probabilistic combination of multiple cues: skin detection, motion detection and foreground extraction.Fast sampling of scalespace over all three modalities is achieved using integral images and parametric models of response distributions are derived using supervised learning techniques.Log likelihood ratios for each modality are combined with spatial priors incorporating tracking and novelty objectives to yield a posterior map indicating the probability of a face appearing at each image location.The result is a real-time attentive visual sensor which reliably fixates faces over a 130 deg field of view, allowing high-resolution capture of facial images over a large dynamic scene.