Three-dimensional object recognition
ACM Computing Surveys (CSUR) - Annals of discrete mathematics, 24
Computational strategies for object recognition
ACM Computing Surveys (CSUR)
A survey of automated visual inspection
Computer Vision and Image Understanding
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IEEE Transactions on Pattern Analysis and Machine Intelligence
Digital Image Processing
The Complex EGI: A New Representation for 3-D Pose Determination
IEEE Transactions on Pattern Analysis and Machine Intelligence
Robust 3-D-3-D Pose Estimation
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Edge-Based Data Structures for Solid Modeling in Curved-Surface Environments
IEEE Computer Graphics and Applications
Monocular body pose estimation by color histograms and point tracking
DAGM'06 Proceedings of the 28th conference on Pattern Recognition
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In this paper, we have attempted to solve the pose estimation problem for a 3-dimensional object by independently estimating the pose parameters through the minimization of a set of objective functions, using Gauss approximation techniques for least squares optimization. In our implementation, the 3-D object is assumed to have three degrees of freedom on a flat surface, which is typical of automated visual inspection applications. However, the solution can be also extended to greater degrees of freedom. We have is shown that the pose can be estimated by only considering the x-coordinates of the known vertices in the projected space, but the same is not true if we consider the y-coordinates alone. We propose a set of modified objective functions from which it is possible to find the pose parameters. The parameters have been determined in noisy conditions under 20-dB and 40-dB SNR values and the robustness of the estimators is confirmed.