Three-dimensional object recognition
ACM Computing Surveys (CSUR) - Annals of discrete mathematics, 24
3DPO: A three-dimensional part orientation system
International Journal of Robotics Research
Automatic Sensor Placement from Vision Task Requirements
IEEE Transactions on Pattern Analysis and Machine Intelligence - Special Issue on Industrial Machine Vision and Computer Vision Technology:8MPart
Computer Vision
CAD-Based Computer Vision: From CAD Models to Relational Graphs
IEEE Transactions on Pattern Analysis and Machine Intelligence
Model-based object recognition in dense-range images—a review
ACM Computing Surveys (CSUR)
Improving Depth Image Acquisition Using Polarized Light
International Journal of Computer Vision
Detecting and localising obstacles in front of a moving vehicle using linear stereo vision
Mathematical and Computer Modelling: An International Journal
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Focuses on the structure of robot sensing systems and the techniques for measuring and preprocessing 3-D data. To get the information required for controlling a given robot function, the sensing of 3-D objects is divided into four basic steps: transduction of relevant object properties (primarily geometric and photometric) into a signal; preprocessing the signal to improve it; extracting 3-D object features; and interpreting them. Each of these steps usually may be executed by several alternative techniques (tools). Tools for the transduction of 3-D data and data preprocessing are surveyed. The performance of each tool depends on the specific vision task and its environmental conditions, both of which are variable. Such a system includes so-called tool-boxes, one box for each sensing step, and a supervisor, which controls iterative sensing feedback loops and consists of a rule-based program generator and a program execution controller. Sensing step sequences and tools are illustrated for two 3-D vision applications at SRI International Company: visually guided robot arc welding and locating identical parts in a bin.