Paper
16 December 2004 Camera sensitivity study
Jonathan Schlueter, Yi Lu Murphey, John W. V. Miller, Malayappan Shridhar, Yun Luo, Farid Khairallah
Author Affiliations +
Abstract
As the cost/performance Ratio of vision systems improves with time, new classes of applications become feasible. One such area, automotive applications, is currently being investigated. Applications include occupant detection, collision avoidance and lane tracking. Interest in occupant detection has been spurred by federal automotive safety rules in response to injuries and fatalities caused by deployment of occupant-side air bags. In principle, a vision system could control airbag deployment to prevent this type of mishap. Employing vision technology here, however, presents a variety of challenges, which include controlling costs, inability to control illumination, developing and training a reliable classification system and loss of performance due to production variations due to manufacturing tolerances and customer options. This paper describes the measures that have been developed to evaluate the sensitivity of an occupant detection system to these types of variations. Two procedures are described for evaluating how sensitive the classifier is to camera variations. The first procedure is based on classification accuracy while the second evaluates feature differences.
© (2004) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jonathan Schlueter, Yi Lu Murphey, John W. V. Miller, Malayappan Shridhar, Yun Luo, and Farid Khairallah "Camera sensitivity study", Proc. SPIE 5606, Two- and Three-Dimensional Vision Systems for Inspection, Control, and Metrology II, (16 December 2004); https://doi.org/10.1117/12.580522
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KEYWORDS
Cameras

Imaging systems

Classification systems

Neural networks

Image analysis

Control systems

Optical filters

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