Gradient-based Camera Exposure Control for Outdoor Mobile Platforms

TL;DR

This paper presents a gradient-based automatic exposure control method for outdoor mobile robot cameras, improving image feature capture under varying illumination for multiple vision tasks.

Contribution

It introduces a novel gradient-based exposure adjustment algorithm and extends it to multi-camera systems for consistent and optimal exposure in outdoor robotics.

Findings

Effective in pedestrian detection and visual odometry

Ensures brightness consistency across multiple cameras

Improves image quality for stereo matching and panoramic imaging

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.