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12 May 2010Online recursive estimation of attention and salient regions in visual scenes
This paper describes an algorithm and system for rapidly generating a saliency map and finding interesting regions and
in large-sized (i.e., extremely high-resolution) imagery and video. Previous methods of finding salient or interesting
regions have a fundamental shortcoming: they need to process the entire image before the saliency map can be outputted
and are therefore very slow for large images. Any prior attempts at parallelizing this operation involve computing feature
maps on separate processors, but these methods cannot provide a result until the entire image has been processed. Rather
than employing a single-step process, our system uses a recursive approach to estimate the saliency, processing parts of
the image in sequence and providing an approximate saliency map for these regions immediately. With each new part of
the image, a series of normalization factors is updated that connects all image parts analyzed so far. As more of the
image parts are analyzed, the saliency map of the previously analyzed parts as well as newly analyzed parts becomes
more exact. In the end, an exact global saliency map of the entire image is available. This algorithm can be viewed as (1)
a fast, parallelizable version of prior art, and/or (2) a new paradigm for computing saliency in large imagery/video. This
is critical, as the analysis of large, high-resolution imagery becomes more commonplace. This system can be employed
in a default, bottom-up manner or a directed, top-down manner which will assign a preference to certain features over
others. One can apply this system to any static scene, whether that is a still photograph or an image captured from video.
Deepak Khosla andDavid J. Huber
"Online recursive estimation of attention and salient regions in visual scenes", Proc. SPIE 7696, Automatic Target Recognition XX; Acquisition, Tracking, Pointing, and Laser Systems Technologies XXIV; and Optical Pattern Recognition XXI, 769614 (12 May 2010); https://doi.org/10.1117/12.850758
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Deepak Khosla, David J. Huber, "Online recursive estimation of attention and salient regions in visual scenes," Proc. SPIE 7696, Automatic Target Recognition XX; Acquisition, Tracking, Pointing, and Laser Systems Technologies XXIV; and Optical Pattern Recognition XXI, 769614 (12 May 2010); https://doi.org/10.1117/12.850758