Journal ArticleDOI
On the recognition of parameterized objects
W. Eric,L. Grimson +1 more
- Vol. 2, Iss: 4, pp 245-253
TLDR
In this paper, a constrained search method was proposed to recognize and locate objects that can vary in parameterized ways, such as two-dimensional objects with rotational, translational, or scaling degrees of freedom.Abstract:
Determining the identity and pose of oceluded objects from noisy data is a critical step in interacting intelligently with an unstructured environment. Previous work has shown that local measurements of position and surface orientation may be used in a constrained search process to solve this problem, for the case of rigid objects, either two-dimensional or three-dimensional. This paper considers the more general problem of recognizing and locating objects that can vary in parameterized ways. We consider two-dimensional objects with rotational, translational, or scaling degrees of freedom, and two-dimensional objects that undergo stretching transformations. We show that the constrained search method can be extended to handle the recognition and localization of such generalized classes of object families.read more
Citations
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Proceedings ArticleDOI
Efficient matching of pictorial structures
TL;DR: An efficient algorithm for finding the best global match of a pictorial stucture to an image is presented and it is shown that this approach is suitable for many generic image recognition problems.
Journal ArticleDOI
Model-based object recognition in dense-range images—a review
Farshid Arman,Jake K. Aggarwal +1 more
TL;DR: This paper presents a comprehensive survey of model-based vision systems using dense-range images using dense -range images to derive an interpretation to complete a specified task.
Journal ArticleDOI
Determining the similarity of deformable shapes
TL;DR: This paper identifies a number of possibly desirable properties of a shape similarity method, and determines the extent to which these properties can be captured by approaches that compare local properties of the contours of the shapes, through elastic matching.
Journal ArticleDOI
Achieving generalized object recognition through reasoning about association of function to structure
Louise Stark,Kevin W. Bowyer +1 more
TL;DR: This is, to the authors' knowledge, the first implemented system to explore the use of a purely function-based definition of an object category (that is, no explicit geometric or structural model) to recognize 3D objects.
Journal ArticleDOI
On the verification of hypothesized matches in model-based recognition
TL;DR: The authors derive an expression for the probability that a randomly occurring match will account for a given fraction of the features of a particular object, a function of the number of model features, theNumber of data features, and bounds on the degree of sensor noise.
References
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Journal ArticleDOI
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Paul J. Besl,Ramesh Jain +1 more
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