1996 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'96)
On a spectral attentional mechanism
San Francisco, Ca.
June 18-June 20
ISBN: 0-8186-7258-7
P. Burlina, Comput. Vision Lab., Maryland Univ., College Park, MD, USA
B. Lin, Comput. Vision Lab., Maryland Univ., College Park, MD, USA
R. Chellappa, Comput. Vision Lab., Maryland Univ., College Park, MD, USA
This paper describes an attentional mechanism based on the interpretation of spectral signatures for detecting regular object configurations in areas of an image delineated using context information. The proposed global operator relies on the spectral analyse's of edge structure and exploits spatial as well as frequency domain constraints derived from known geometrical models of monitored objects. A decision theoretic method for learning decision regions is presented. Applications of this mechanism are demonstrated for several aerial image interpretation tasks. Specific examples are described for detecting vehicle formations (such as convoys), qualifying the geometry of detected formations, or monitoring the occupancy of regions of interest (such as parking areas, roads, or open areas). Experiments and sensitivity analysis results are reported.
Index Terms:
edge detection; sensitivity analysis; object detection; decision theory; spectral attentional mechanism; spectral signatures; regular object configurations; context information; global operator; frequency domain constraints; geometrical models; monitored objects; decision theoretic method; learning decision regions; aerial image interpretation tasks; vehicle formations; convoys; detected formations; sensitivity analysis
Citation:
P. Burlina, B. Lin, R. Chellappa, "On a spectral attentional mechanism," cvpr, pp.120, 1996 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'96), 1996
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