Gradient-based Camera Exposure Control for Outdoor Mobile Platforms
Inwook Shim, Tae-Hyun Oh, Joon-Young Lee, Jinwook Choi, Dong-Geol Choi, In So Kweon
- Year
- 2017
- Access
- Open access
Abstract
We introduce a novel method to automatically adjust camera exposure for image processing and computer vision applications on mobile robot platforms. Because most image processing algorithms rely heavily on low-level image features that are based mainly on local gradient information, we consider that gradient quantity can determine the proper exposure level, allowing a camera to capture the important image features in a manner robust to illumination conditions. We then extend this concept to a multi-camera system and present a new control algorithm to achieve both brightness consistency between adjacent cameras and a proper exposure level for each camera. We implement our prototype system with off-the-shelf machine-vision cameras and demonstrate the effectiveness of the proposed algorithms on practical applications, including pedestrian detection, visual odometry, surround-view imaging, panoramic imaging and stereo matching.
Keywords
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