TY  - CONF
AU  - Miguel Oliveira
AU  - Angel Sappa
AU  - V. Santos
A2  - IV
PY  - 2012//
TI  - Color Correction for Onboard Multi-camera Systems  using 3D Gaussian Mixture Models
BT  - IEEE Intelligent Vehicles Symposium
SP  - 299
EP  - 303
PB  - IEEE Xplore
N2  - The current paper proposes a novel color correction approach for onboard multi-camera systems. It works by segmenting the given images into several regions. A probabilistic segmentation framework, using 3D Gaussian Mixture Models, is proposed. Regions are used to compute local color correction functions, which are then combined to obtain the final corrected image. An image data set of road scenarios is used to establish a performance comparison of the proposed method with other seven well known color correction algorithms. Results show that the proposed approach is the highest scoring color correction method. Also, the proposed single step 3D color space probabilistic segmentation reduces processing time over similar approaches.
SN  - 1931-0587
SN  - 978-1-4673-2119-8
L1  - http://refbase.cvc.uab.es/files/OSS2012b.pdf
UR  - http://dx.doi.org/10.1109/IVS.2012.6232141
N1  - ADAS
ID  - Miguel Oliveira2012
ER  -