Title :
On a spectral attentional mechanism
Author :
Burlina, Philippe ; Lin, Bruce ; Chellappa, Rama
Author_Institution :
Comput. Vision Lab., Maryland Univ., College Park, MD, USA
Abstract :
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
Keywords :
decision theory; edge detection; object detection; sensitivity analysis; aerial image interpretation tasks; context information; convoys; decision theoretic method; detected formations; frequency domain constraints; geometrical models; global operator; learning decision regions; monitored objects; regular object configurations; sensitivity analysis; spectral attentional mechanism; spectral signatures; vehicle formations; Frequency domain analysis; Geometry; Image edge detection; Monitoring; Object detection; Road vehicles; Sensitivity analysis; Solid modeling; Spectral analysis; Vehicle detection;
Conference_Titel :
Computer Vision and Pattern Recognition, 1996. Proceedings CVPR '96, 1996 IEEE Computer Society Conference on
Conference_Location :
San Francisco, CA
Print_ISBN :
0-8186-7259-5
DOI :
10.1109/CVPR.1996.517063