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Titlebook: Computer Vision - ECCV 2014 Workshops; Zurich, Switzerland, Lourdes Agapito,Michael M. Bronstein,Carsten Rothe Conference proceedings 2015

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Conference proceedings 2015perception of affordance and functional visual primitives for scene analysis; graphical models in computer vision; light fields for computer vision; computer vision for road scene understanding and autonomous driving; soft biometrics; transferring and adapting source knowledge in computer vision; su
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R. Angus Harkness,Forrester Cockburn with patients and elderly from remote locations. However, using such systems can be a difficult task particularly for caregivers without proper training. The paper presents a first implementation of a vision-based cooperative driving enhancement to a telepresence robot. A preliminary evaluation in the laboratory environment is presented.
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Problems of Passive Resistance,stics needed for phenotyping of plants, but it also provides a solution to the problem of overlapping roots in the images. Using a Reeb graph based representation, such overlaps can be directly detected without further analysis, during the computation of the graph.
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Combining Semi-autonomous Navigation with Manned Behaviour in a Cooperative Driving System for Mobil with patients and elderly from remote locations. However, using such systems can be a difficult task particularly for caregivers without proper training. The paper presents a first implementation of a vision-based cooperative driving enhancement to a telepresence robot. A preliminary evaluation in the laboratory environment is presented.
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Representing Roots on the Basis of Reeb Graphs in Plant Phenotypingstics needed for phenotyping of plants, but it also provides a solution to the problem of overlapping roots in the images. Using a Reeb graph based representation, such overlaps can be directly detected without further analysis, during the computation of the graph.
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Distortion Correction in 3D-Modeling of Root Systems for Plant Phenotypingants. As our results demonstrate, our method provides an accurate 3D point cloud containing the coordinates of the surface of the root system with error smaller than 0.16 mm in average and standard deviation of less than 0.13 mm.
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