Multisensor Object Recognition From 3D Models

Tom Miltonberger; Doug Morgan; Greg Orr

doi:10.1117/12.948927

5 January 1989 Multisensor Object Recognition From 3D Models

Tom Miltonberger, Doug Morgan, Greg Orr

Proceedings Volume 1003, Sensor Fusion: Spatial Reasoning and Scene Interpretation; (1989) https://doi.org/10.1117/12.948927
Event: 1988 Cambridge Symposium on Advances in Intelligent Robotics Systems, 1988, Boston, MA, United States

Abstract

Multisensor fusion for object recognition, particularly when multiple sensor platforms and phenomenologies are considered, stresses the state of the art in model-based Image Understanding. The discrimination power of the algorithms depends on accumulation of evidence from diverse sources and on properly applying known model constraints to sensor data. In this paper we describe a model-based multiple-hypothesis Bayesian approach to recognition that has roots in detection and estimation theory. We also describe an approach to object modeling that utilizes an object-based representation that allows multiple geometric representations and multiple, alternative decompositions of the object model. Initial implementations of these ideas have been incorporated into a model-based vision testbed and are currently undergoing testing and evaluation.

Citation Download Citation

Tom Miltonberger, Doug Morgan, and Greg Orr "Multisensor Object Recognition From 3D Models", Proc. SPIE 1003, Sensor Fusion: Spatial Reasoning and Scene Interpretation, (5 January 1989); https://doi.org/10.1117/12.948927

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