Active Control of Camera Parameters for Object Detection Algorithms
This addresses robustness in robot vision under varying light conditions, but is incremental as it builds on existing auto-exposure methods.
The paper tackled the problem of camera parameters affecting object detection performance for vision-guided robots, proposing an active control method that improved performance compared to conventional auto-exposure algorithms.
Camera parameters not only play an important role in determining the visual quality of perceived images, but also affect the performance of vision algorithms, for a vision-guided robot. By quantitatively evaluating four object detection algorithms, with respect to varying ambient illumination, shutter speed and voltage gain, it is observed that the performance of the algorithms is highly dependent on these variables. From this observation, a novel active control of camera parameters method is proposed, to make robot vision more robust under different light conditions. Experimental results demonstrate the effectiveness of our proposed approach, which improves the performance of object detection algorithms, compared with the conventional auto-exposure algorithm.