Qualitative Reasoning Feeding Back into Quantitative Model-Based Tracking

Tracking vehicles in image sequences of innercity road traffic scenes still constitutes a challenging task. Even if a-priori knowledge about the 3D shape of vehicles, of background structure and vehicle motion is provided, (partial) occlusion and dense vehicle queues easily can cause initialization and tracking failures. Improving the tracking approach requires numerous and time-consuming experiments. Yet, these difficulties can be eased considerably by endowing the system with a part of the qualitative knowledge, that a human observer uses in order to judge the results. In the case reported here, a system for qualitative reasoning has been coupled with a quantitative model-based tracking system in order to explore the feedback from qualitative reasoning into the geometric tracking subsystem.

• Type: Conference
• Year: 2004
• Where: ECAI
• Authors: Christian Köhler, Artur Ottlik, Hans-Hellmut Nagel, Bernhard Nebel
• Keywords: Artificial Intelligence, ECAI 2004, Innercity Road Traffic, Qualitative Reasoning, Quantitative Model-based Tracking