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Download fileImproving Spatial Support for Objects via Multiple Segmentations
journal contribution
posted on 2007-01-01, 00:00 authored by Tomasz Malisiewicz, Alexei A EfrosSliding window scanning is the dominant paradigm in object recognition research
today. But while much success has been reported in detecting several
rectangular-shaped object classes (i.e. faces, cars, pedestrians), results have
been much less impressive for more general types of objects. Several researchers
have advocated the use of image segmentation as a way to get a
better spatial support for objects. In this paper, our aim is to address this issue
by studying the following two questions: 1) how important is good spatial
support for recognition? 2) can segmentation provide better spatial support
for objects? To answer the first, we compare recognition performance using
ground-truth segmentation vs. bounding boxes. To answer the second,
we use the multiple segmentation approach to evaluate how close can real
segments approach the ground-truth for real objects, and at what cost. Our
results demonstrate the importance of finding the right spatial support for objects,
and the feasibility of doing so without excessive computational burden.