Multisensor Fusion for Automatic Scene Interpretation

  • J. K. Aggarwa
  • N. Nandhakumar
Part of the Springer Series in Perception Engineering book series (SSPERCEPTION)


The area of computer analysis of images for automated detection and classification of objects in a scene has been intensively researched in the recent past. Two kinds of approaches may be noted in current and past research in machine perception - (1) To model the functions of biological vision systems, e.g., edge detection by the human visual system, and (2) To develop a scheme which a machine can use for accomplishing a particular task, e.g. automated detection of faulty placement of components on a printed circuit board. The latter approach produces a scheme that is application specific. In developing a scheme for a particular machine perception task one has a wide choice of sensing modalities and techniques to interpret the sensed signals. One is not limited by characteristics of a biological vision system that one is forced to emulate in the first approach, not even by the restriction that system emulate only the observed behavior of the biological system.


Surface Heat Flux Image Model Range Image Visual Imagery Outdoor Scene 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag New York, Inc. 1990

Authors and Affiliations

  • J. K. Aggarwa
  • N. Nandhakumar
    • 1
  1. 1.Computer and Vision Research CenterThe University of Texas at AustinAustinUSA

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