Ph.D student, ECE Dept, University of Maryland
liyi AT umiacs DOT umd DOT edu
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Ph.D student, ECE Dept, University of Maryland liyi AT umiacs DOT umd DOT edu |
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Visual perception of the intensity
The contrast effect and its counterpart, the assimilation effect, paradoxically co-exist in intensity perception. It is natural to assume that there is a single structural mechanism that accounts to both effects. However, despite there is a large body of work studying individual illusions, the link between them is not well understood. Here, we propose a computational model using L1 minimization. Analog to the Ganglion cell in the visual path, the intensity of the stimulus is compressed by simple local average filters at random positions. This process can be formulated using an underdetermined linear system. Assuming the signal is sparse in the Fourier domain, the decoder finds the sparse solution of this system in the reconstruction phase. Experiments show that the contrast and the assimilation effect are the artifacts during the signal reconstruction, which suggests that both effects are the two sides of the same coin
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Vision Based Robot Mobile robots must have the ability to navigate autonomously and recognize objects in a previously-unknown indoor environment in many tasks. However, state-of-the-art techniques in robotics and in computer vision are not used together to achieve this goal. In this paper, we present a complete system that segments objects and utilizes the online image datasets for object recognition during navigation. Equipped with a quad camera, the mobile platform explores an unknown indoor area using SLAM, and separates the object from the background actively. Shape-based matching is performed on a set of shape images and the detected objects are highlighted with a bounding box and semantic label. Paper:
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