The paper presents an approach for detecting vehicles in urban traffic scenes by means of rule-based reasoning on visual data. The strength of the approach is its formal separation between the low-level image processing modules (used for extracting visual data under various illumination conditions) and the high-level module, which provides a general-purpose knowledge-based framework for tracking vehicles in the scene. The image-processing modules extract visual data from the scene by spatio-temporal analysis during daytime, and by morphological analysis of headlights at night, The high-level module is designed as a forward chaining production rule system, working on symbolic data, i.e., vehicles and their attributes (area, pattern, direction, and others) and exploiting a set of heuristic rules tuned to urban traffic conditions, The synergy between the artificial intelligence techniques of the high-level and the low-level image analysis techniques provides the system with flexibility and robustness.

Image Analysis and Rule-Based Reasoning for a Traffic Monitoring / Cucchiara, Rita; M., Piccardi; P., Mello. - In: IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS. - ISSN 1524-9050. - ELETTRONICO. - 1(2):(2000), pp. 119-130.

Image Analysis and Rule-Based Reasoning for a Traffic Monitoring

CUCCHIARA, Rita;
2000

Abstract

The paper presents an approach for detecting vehicles in urban traffic scenes by means of rule-based reasoning on visual data. The strength of the approach is its formal separation between the low-level image processing modules (used for extracting visual data under various illumination conditions) and the high-level module, which provides a general-purpose knowledge-based framework for tracking vehicles in the scene. The image-processing modules extract visual data from the scene by spatio-temporal analysis during daytime, and by morphological analysis of headlights at night, The high-level module is designed as a forward chaining production rule system, working on symbolic data, i.e., vehicles and their attributes (area, pattern, direction, and others) and exploiting a set of heuristic rules tuned to urban traffic conditions, The synergy between the artificial intelligence techniques of the high-level and the low-level image analysis techniques provides the system with flexibility and robustness.
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Image Analysis and Rule-Based Reasoning for a Traffic Monitoring / Cucchiara, Rita; M., Piccardi; P., Mello. - In: IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS. - ISSN 1524-9050. - ELETTRONICO. - 1(2):(2000), pp. 119-130.
Cucchiara, Rita; M., Piccardi; P., Mello
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11380/449695
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