This paper describes the automatic selection of features from an image training set using the theories of multi-dimensional linear discriminant analysis and the associated optimal linear projection. We demonstrate the effectiveness of these Most Discriminating Features for view-based class

The paper presents a review of 200 references in content-based image retrieval. The paper starts with discussing the working conditions of content-based retrieval: patterns of use, types of pictures, the role of semantics, and the sensory gap. Subsequent sections discuss computational steps

We present a 3-D shape-based object recognition system for simultaneous recognition of multiple objects in scenes containing clutter and occlusion. Recognition is based on matching surfaces by matching points using the spin-image representation. The spin-image is a data level shape descriptor

We present a novel approach to measuring similarity between shapes and exploit it for object recognition. In our framework, the measurement of similarity is preceded by (1) solv- ing for correspondences between points on the two shapes, (2) using the correspondences to estimate an aligning

environments we show that very simple visual features can be used to represent the perception/action relation specific to a given behavior. From this point we propose a learning model relying on a statistical collection of two-pixels features for representing a behavior. We then present the experiments made

the biological feasibility of this class of models to explain higher level visual processing, such as object recognition. We describe a new hierarchical model that accounts well for this complex visual task, is consistent with several recent physiological experiments in inferotemporal cortex and makes testable

in office environments we show that very simple visual features can be used to represent the perception/action relation specific to a given behavior. From this point we propose a learning model relying on a statistical collection of two-pixels features for representing a behavior. We then present

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This paper provides a comprehensive survey of the technical achievements in the research area of image retrieval, especially content-based image retrieval, an area that has been so active and prosperous in the past few years. The survey includes 100+ papers covering the research aspects of image

Image-space simplifications have been used to accelerate the calculation of computer graphic images since the dawn of visual simulation. Texture mapping has been used to provide a means by which images may themselves be used as display primitives. The work reported by this paper endeavors to carry