Now showing items 1-6 of 6
On the Verification of Hypothesized Matches in Model-Based Recognition
In model-based recognition, ad hoc techniques are used to decide if a match of data to model is correct. Generally an empirically determined threshold is placed on the fraction of model features that must be matched. ...
On the Recognition of Parameterized Objects
Determining the identity and pose of occluded 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 ...
On the Recognition of Curved Objects
Determining the identity and pose of occluded objects from noisy data is a critical part of a system's intelligent interaction with an unstructured environment. Previous work has shown that local measurements of the ...
The Combinatorics of Heuristic Search Termination for Object Recognition in Cluttered Environments
Many recognition systems use constrained search to locate objects in cluttered environments. Earlier analysis showed that the expected search is quadratic in the number of model and data features, if all the data comes ...
Recognition and Localization of Overlapping Parts from Sparse Data
This paper discusses how sparse local measurements of positions and surface normals may be used to identify and locate overlapping objects. The objects are modeled as polyhedra (or polygons) having up to six degreed ...
On the Sensitivity of the Hough Transform for Object Recognition
A common method for finding an object's pose is the generalized Hough transform, which accumulates evidence for possible coordinate transformations in a parameter space and takes large clusters of similar transformations ...