Robust component-based car detection in aerial imagery with new segmentation techniques

Yueh Ouyang; Pierre-Luc Duval; Yunlong Sheng; Daniel A. Lavigne

doi:10.1117/12.884356

25 May 2011 Robust component-based car detection in aerial imagery with new segmentation techniques

Yueh Ouyang, Pierre-Luc Duval, Yunlong Sheng, Daniel A. Lavigne

Proceedings Volume 8020, Airborne Intelligence, Surveillance, Reconnaissance (ISR) Systems and Applications VIII; 80200M (2011) https://doi.org/10.1117/12.884356
Event: SPIE Defense, Security, and Sensing, 2011, Orlando, Florida, United States

Abstract

Several new techniques are introduced to the component-based vehicle detection in the aerial imagery. The shape-independent tricolour attenuation model based on the spectral power density difference between the regions lighted by direct sunlight and/or diffuse skylight is used to identify cast shadows. The simple linear iterative clustering (SLIC) performs local clustering for superpixels, which were merged by a statistical region merging (SRM) method based on the independent bounded difference inequality theorem. The car body parts were found with Support Vector Machine based on the radiometric and geometric features of the segmented regions. All the algorithms used in this approach require minimum human intervention, providing a robust detection.

Citation Download Citation

Yueh Ouyang, Pierre-Luc Duval, Yunlong Sheng, and Daniel A. Lavigne "Robust component-based car detection in aerial imagery with new segmentation techniques", Proc. SPIE 8020, Airborne Intelligence, Surveillance, Reconnaissance (ISR) Systems and Applications VIII, 80200M (25 May 2011); https://doi.org/10.1117/12.884356

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