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IJCV
2000

Recognition without Correspondence using Multidimensional Receptive Field Histograms

13 years 3 months ago
Recognition without Correspondence using Multidimensional Receptive Field Histograms
The appearance of an object is composed of local structure. This local structure can be described and characterized by a vector of local features measured by local operators such as Gaussian derivatives or Gabor filters. This article presents a technique where appearances of objects are represented by the joint statistics of such local neighborhood operators. As such, this represents a new class of appearance based techniques for computer vision. Based on joint statistics, the paper develops techniques for the identification of multiple objects at arbitrary positions and orientations in a cluttered scene. Experiments show that these techniques can identify over 100 objects in the presence of major occlusions. Most remarkably, the techniques have low complexity and therefore run in real-time.
Bernt Schiele, James L. Crowley
Added 18 Dec 2010
Updated 18 Dec 2010
Type Journal
Year 2000
Where IJCV
Authors Bernt Schiele, James L. Crowley
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