The feasibility test of state-of-the-art face detection algorithms for vehicle occupant detection

Andrey Makrushin; Jana Dittmann; Claus Vielhauer; Mirko Langnickel; Christian Kraetzer

doi:10.1117/12.838964

8 February 2010 The feasibility test of state-of-the-art face detection algorithms for vehicle occupant detection

Andrey Makrushin, Jana Dittmann, Claus Vielhauer, Mirko Langnickel, Christian Kraetzer

Proceedings Volume 7532, Image Processing: Algorithms and Systems VIII; 75320V (2010) https://doi.org/10.1117/12.838964
Event: IS&T/SPIE Electronic Imaging, 2010, San Jose, California, United States

Abstract

Vehicle seat occupancy detection systems are designed to prevent the deployment of airbags at unoccupied seats, thus avoiding the considerable cost imposed by the replacement of airbags. Occupancy detection can also improve passenger comfort, e.g. by activating air-conditioning systems. The most promising development perspectives are seen in optical sensing systems which have become cheaper and smaller in recent years. The most plausible way to check the seat occupancy by occupants is the detection of presence and location of heads, or more precisely, faces. This paper compares the detection performances of the three most commonly used and widely available face detection algorithms: Viola- Jones, Kienzle et al. and Nilsson et al. The main objective of this work is to identify whether one of these systems is suitable for use in a vehicle environment with variable and mostly non-uniform illumination conditions, and whether any one face detection system can be sufficient for seat occupancy detection. The evaluation of detection performance is based on a large database comprising 53,928 video frames containing proprietary data collected from 39 persons of both sexes and different ages and body height as well as different objects such as bags and rearward/forward facing child restraint systems.

Citation Download Citation

Andrey Makrushin, Jana Dittmann, Claus Vielhauer, Mirko Langnickel, and Christian Kraetzer "The feasibility test of state-of-the-art face detection algorithms for vehicle occupant detection", Proc. SPIE 7532, Image Processing: Algorithms and Systems VIII, 75320V (8 February 2010); https://doi.org/10.1117/12.838964

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