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In this paper, autonomous switching between two basic attention selection mechanisms, i.e., top-down and bottom-up, is proposed. This approach fills a gap in object search using conventional top-down biased bottom-up attention selection, which fails, if a group of objects is searched whose appearances cannot be uniquely described by low-level features used in bottom-up computational models. Three...
In this paper an autonomous switching between two basic attention selection mechanisms, top-down and bottom-up, is proposed, substituting manual switching. This approach fills the gab in object search using conventional top-down biased bottom-up attention selection: the latter one fails, if a group of objects is searched whose appearances can not be uniquely described by low-level features used in...
In the autonomous city explorer (ACE) project a mobile robot is developed, which is capable of finding its way to a given destination in an unknown urban environment. An exemplary mission is to find the way from our institute to the Marienplatz, a public place in the center of Munich, without any prior knowledge or GPS information. Inspired by the behavior of humans in unknown environments, ACE must...
In this paper a novel implementation of the saliency map model on a multi-GPU platform using CUDA technology is presented. The saliency map model is a well-known computational model for bottom-up attention selection and serves as a basis of many attention control strategies of cognitive vision systems. A real-time implementation is the prerequisite of an application of bottom-up attention on mobile...
A biologically inspired foveated attention system in an object detection scenario is proposed. Thereby, a high-performance active multi-focal camera system imitates visual behaviors such as scan, saccade and fixation. Bottom-up attention uses wide-angle stereo data to select a sequence of fixation points in the peripheral field of view. Successive saccade and fixation of high foveal resolution using...
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. This paper focuses on coordination mechanisms of top-down and bottom-up attentional allocation, with particular consideration of the current local environment. The top-down attention selection in the task-space...
Inspired by the expectation-based perception of humans, a surprise-driven active vision system is proposed. This vision system not only considers spatial saliency of objects in the environment, but also investigates temporal novelty in the neighborhood. Surprise is defined as the difference of the saliency probability distributions of two consecutive input images, which is measured using Kullback-Leibler...
A multi-camera view direction planning strategy for mobile robots is discussed. Two concurrent tasks are considered: self-localization and object tracking. The approach is to assign the different tasks to different cameras, such that for each task an individual optimal view direction is selected based on the information gain maximization. Thereby, the individual task performance is significantly improved...
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