Stereo Camera

Stereo cameras, utilizing two lenses to mimic human binocular vision, are central to numerous applications requiring 3D scene understanding. Current research focuses on improving accuracy and efficiency in tasks like depth estimation, object detection and tracking, and navigation, often employing deep learning architectures such as Transformers and neural networks operating on voxel or point cloud representations. These advancements are driving progress in robotics (autonomous navigation), augmented/virtual reality (facial motion capture), and autonomous driving (vehicle velocity estimation and environment mapping), where accurate and real-time 3D perception is crucial. The development of robust and efficient stereo vision systems is thus a significant area of ongoing research with broad practical implications.