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Inferring 3D Shapes from 2D Codons
(1985-04-01)
All plane curves can be described at an abstract level by a sequence of five primitive elemental shapes, called "condons", which capture the sequential relations between the singular points of curvature. The condon ...
Codon Constraints on Closed 2D Shapes
(1984-05-01)
Codons are simple primitives for describing plane curves. They thus are primarily image-based descriptors. Yet they have the power to capture important information about the 3-D world, such as making part boundaries ...
Direction Estimation of Pedestrian from Images
(2003-08-27)
The capability of estimating the walking direction of people would be useful in many applications such as those involving autonomous cars and robots.We introduce an approach for estimating the walking direction of people ...
Contextual Priming for Object Detection
(2001-09-01)
There is general consensus that context can be a rich source of information about an object's identity, location and scale. In fact, the structure of many real-world scenes is governed by strong configurational rules akin ...
Dissociated Dipoles: Image representation via non-local comparisons
(2003-08-13)
A fundamental question in visual neuroscience is how to represent image structure. The most common representational schemes rely on differential operators that compare adjacent image regions. While well-suited to encoding ...
Gait Dynamics for Recognition and Classification
(2001-09-01)
This paper describes a representation of the dynamics of human walking action for the purpose of person identification and classification by gait appearance. Our gait representation is based on simple features such as ...
3D Object Recognition: Symmetry and Virtual Views
(1992-12-01)
Many 3D objects in the world around us are strongly constrained. For instance, not only cultural artifacts but also many natural objects are bilaterally symmetric. Thoretical arguments suggest and psychophysical ...
Dissociated Dipoles: Image representation via non-local comparisons
(2003-08-13)
A fundamental question in visual neuroscience is how to represent image structure. The most common representational schemes rely on differential operators that compare adjacent image regions. While well-suited to encoding ...
Complex Feature Recognition: A Bayesian Approach for Learning to Recognize Objects
(1996-11-01)
We have developed a new Bayesian framework for visual object recognition which is based on the insight that images of objects can be modeled as a conjunction of local features. This framework can be used to both derive ...
Correspondence and Affine Shape from Two Orthographic Views: Motion and Recognition
(1991-12-01)
The paper presents a simple model for recovering affine shape and correspondence from two orthographic views of a 3D object. It is shown that four corresponding points along two orthographic views, taken under similar ...