Hybrid pyramid/neural network object recognition

P. Anandan; Peter J. Burt; John C. Pearson; Clay D. Spence

doi:10.1117/12.169460

25 February 1994 Hybrid pyramid/neural network object recognition

P. Anandan, Peter J. Burt, John C. Pearson, Clay D. Spence

Proceedings Volume 2103, 22nd AIPR Workshop: Interdisciplinary Computer Vision: Applications and Changing Needs; (1994) https://doi.org/10.1117/12.169460
Event: 22nd Applied Imagery Pattern Recognition Workshop, 1993, Washington, DC, United States

Abstract

This work concerns computationally efficient computer vision methods for the search for and identification of small objects in large images. The approach combines neural network pattern recognition with pyramid-based coarse-to-fine search, in a way that eliminates the drawbacks of each method when used by itself and, in addition, improves object identification through learning and exploiting the low-resolution image context associated with the objects. The presentation will describe the system architecture and the performance on illustrative problems.

Citation Download Citation

P. Anandan, Peter J. Burt, John C. Pearson, and Clay D. Spence "Hybrid pyramid/neural network object recognition", Proc. SPIE 2103, 22nd AIPR Workshop: Interdisciplinary Computer Vision: Applications and Changing Needs, (25 February 1994); https://doi.org/10.1117/12.169460

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