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Robust and Efficient 3D Recognition by Alignment
Alignment is a prevalent approach for recognizing 3D objects in 2D images. A major problem with current implementations is how to robustly handle errors that propagate from uncertainties in the locations of image ...
Limitations of Geometric Hashing in the Presence of Gaussian Noise
This paper presents a detailed error analysis of geometric hashing for 2D object recogition. We analytically derive the probability of false positives and negatives as a function of the number of model and image, ...
Space Efficient 3D Model Indexing
We show that we can optimally represent the set of 2D images produced by the point features of a rigid 3D model as two lines in two high-dimensional spaces. We then decribe a working recognition system in which we ...
Recognizing 3D Ojbects of 2D Images: An Error Analysis
Many object recognition systems use a small number of pairings of data and model features to compute the 3D transformation from a model coordinate frame into the sensor coordinate system. With perfect image data, these ...
Recognition and Structure from One 2D Model View: Observations on Prototypes, Object Classes and Symmetries
In this note we discuss how recognition can be achieved from a single 2D model view exploiting prior knowledge of an object's structure (e.g. symmetry). We prove that for any bilaterally symmetric 3D object one non- ...