Visual attention Control
Human and animals do not look at a scene in a steady way. Their eyes shift very fast to locate interesting parts of the scene, which is well known as saccade. This cognitive process of selectively concentrating on one aspect of the environment while ignoring other things is called attention. Studies about human visual perception show that visual attention selection is effected by two distinct types of attentional mechanisms: top-down and bottom-up. Top-down signals are derived from task specification, while bottom-up signals are caused by salient stimuli.
Goal-directed guidance of gaze control based on coordinated task and stimulus parameters is essential for steering a mobile cognitive system efficiently and autonomously through the real world. Our research focuses on coordination mechanisms of top-down and bottom-up attentional allocation, with particular consideration of the familiarity of the current local environment. Fig. 1 illustrates the image sequence and the respective camera view directions. The robot directed its attention to task-relevant information (top-down) – the landmarks -- in a familiar context, and located the surprising event (bottom-up) – the human showing up in the fifth image – in a less familiar context.

GPU-aided Image Processing
In the last few years, the programmable GPUs have become more and more popular. GPU is specialized for compute-intensive, highly parallel computation. Moreover, the Compute Unified Device Architecture (CUDA), a new hardware and software architecture issued by NVIDIA in 2007, allows issuing and managing computations on the GPU as a data-parallel computing device without the need of mapping them in a graphics API. We can achieve the real-time image processing facilitated by GPUs.
Researcher
Tingting Xu
Kolja Kühnlenz