Camera Selection

Camera selection optimizes the use of multiple cameras in various applications, aiming to reduce computational costs, improve accuracy, and enhance energy efficiency. Current research focuses on developing algorithms, often employing deep learning networks and reinforcement learning, to intelligently select the most informative camera views based on factors like occlusion, scene content, and energy consumption. These advancements are significant for improving the performance of computer vision tasks such as 3D pose estimation, object tracking, and video-based person re-identification, while simultaneously reducing resource demands in real-world deployments.