Feature association within a multiple-camera system

Archana Sangole; George K. Knopf

doi:10.1117/12.467716

18 October 2002 Feature association within a multiple camera system

Archana Sangole, George K. Knopf

Author Affiliations +

Proceedings Volume 4902, Optomechatronic Systems III; (2002) https://doi.org/10.1117/12.467716
Event: Optomechatronic Systems III, 2002, Stuttgart, Germany

Abstract

Multiple off-the-shelf cameras can be configured to simultaneously provide redundant data, complementary information, and fast processing through sensor parallelism. The redundancy in the captured data can increase the accuracy of scene interpretation and improve system reliability by reducing the overall uncertainty associated with feature classification. Complementary information extracted from several cameras allows novel features in the environment to be identified that are normally impossible to detect with an individual CCD camera or range scanner. An unsolved problem in using multiple cameras for part identification or fault detection is associating the image features captured by one camera with that from another camera, or the same camera at a different point in time. In this paper, a spherical self-organizing feature map (SOFM) is used to combine and correlate both redundant and complementary features extracted from the images acquired by a multiple camera system. An important feature of the proposed technique is that the spherical SOFM develops a topologically ordered representation of the feature vectors derived from a high-dimensional input space. The unsupervised learning algorithm exploits hidden redundancies in the data set and ensures that 'similar' feature vectors will be assigned to cluster units that lie in identifiable neighborhoods on the spherical lattice. To illustrate the proposed methodology, a spherical SOFM that classifies the feature vectors acquired by a trinocular camera system is described.

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Archana Sangole and George K. Knopf "Feature association within a multiple camera system", Proc. SPIE 4902, Optomechatronic Systems III, (18 October 2002); https://doi.org/10.1117/12.467716

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KEYWORDS

Cameras

Spherical lenses

Sensors

Feature extraction

Imaging systems

Data fusion

CCD cameras

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