In recent years, computer vision research has been strongly influenced by latest developments in the fields of artificial intelligence and deep learning. In this talk, we focus on computer vision algorithms for 2D and 3D environment perception in the context of assisted/autonomous driving and human-robot interaction. An important goal is to design algorithms that learn to reconstruct and interpret different types of traffic or robotic scenes based on large collections of suitable training data. Also, in the vision-based analysis of human motion and recognition of a person's expression/intention is gaining importance, in order to achieve trustworthy human-machine interaction and high user comfort. We discuss current trends and research challenges in the context of human-machine interaction along with potential societal implications.
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