Three-dimensional object recognition
ACM Computing Surveys (CSUR) - Annals of discrete mathematics, 24
Robotics: control, sensing, vision, and intelligence
Robotics: control, sensing, vision, and intelligence
Segmentation through Variable-Order Surface Fitting
IEEE Transactions on Pattern Analysis and Machine Intelligence
Active optical range imaging sensors
Advances in Machine Vision
On Three-Dimensional Surface Reconstruction Methods
IEEE Transactions on Pattern Analysis and Machine Intelligence
Model-based object recognition in dense-range images—a review
ACM Computing Surveys (CSUR)
The Role of Model-Based Segmentation in the Recovery of Volumetric Parts From Range Data
IEEE Transactions on Pattern Analysis and Machine Intelligence
COSMOS-A Representation Scheme for 3D Free-Form Objects
IEEE Transactions on Pattern Analysis and Machine Intelligence
Robust Adaptive Segmentation of Range Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Using Spin Images for Efficient Object Recognition in Cluttered 3D Scenes
IEEE Transactions on Pattern Analysis and Machine Intelligence
Edge detection in range images based on scan line approximation
Computer Vision and Image Understanding
The Complex EGI: A New Representation for 3-D Pose Determination
IEEE Transactions on Pattern Analysis and Machine Intelligence
Gradient-based polyhedral segmentation for range images
Pattern Recognition Letters
A Method for Tracking the Pose of Known 3-D Objects Based on an Active Contour Model
ICPR '96 Proceedings of the 1996 International Conference on Pattern Recognition (ICPR '96) Volume I - Volume 7270
Eigen Space Approach for a Pose Detection with Range Images
ICPR '96 Proceedings of the 1996 International Conference on Pattern Recognition (ICPR '96) Volume I - Volume 7270
Range-data-based object surface segmentation via edges and critical points
IEEE Transactions on Image Processing
Range image segmentation using a relaxation oscillator network
IEEE Transactions on Neural Networks
On-Line 3D Geometric Model Reconstruction
ICCS '08 Proceedings of the 8th international conference on Computational Science, Part II
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Three-dimensional (3D) image processing provides a useful tool for machine vision applications. Typically a 3D vision system is divided into data acquisition, low-level processing, object representation and matching. In this paper, a 3D object pose estimation method is developed for an automated manufacturing assembly process. The experimental results show that the 3D pose estimation method produces accurate geometrical information for an automated material handling application.