Advances in computer vision propel transportation autonomy
Vision is a powerful human sensory input. It enables complex tasks and processes we take for granted. With an increase in AoT™ (Autonomy of Things) in diverse applications ranging from transportation and agriculture to robotics and medicine, the role of cameras, computing and machine learning in providing human-like vision and cognition is becoming significant. Computer vision as an academic discipline took off in the 1960s, primarily at universities engaged in the emerging field of artificial intelligence (AI) and machine learning. It progressed dramatically in the next four decades as significant advances in semiconductor and computing technologies were made. Recent advances in deep learning and artificial intelligence have further accelerated the application of computer vision to provide real-time, low latency perception and cognition of the environment, enabling autonomy, safety and efficiency in various applications. Transportation is one area that has benefitted significantly.