Machine Learning and Robot Perception - Bruno Apolloni et al (Eds) Part 11 pot
... micro-facets where each facet is assumed to be one side of a symmetric V-cavity. The set of micro-facets has a mean normal vector of n, and a random variable α is used to represent the angle between each ... 1992. [9] F. Blais and M. Rioux. Real-time numerical peak detector. Signal Processing, 11: 145–155, 1986. [10] J-D Boissonnat. Geometric structure for three-dimensional shape rep- re...
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... global and/ or local object specific detail. Global details do not have a precise geometric location in- side the object, such as statistics of gray levels or colors, textures, etc. Lo- cal details ... symbols: capital letters, small letters, and numbers and icons like emergency exits, stairs, elevators, fire extinguishing materials, etc. The weight sets are tried se- quentially until...
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... Mueller R. Etienne-Cummings, J.Van der Spiegel and Mao-Zhu Zhang, “A foveated silicon retina for two-dimensional tracking”, IEEE Trans. on Circuits and Systems II: Analog and Digital Signal Processing, ... spatial domain vision op- erations. Next section presents classic vision algorithms (space-variant op- tical flow, stereo disparity, anisotropic diffusion, corner detection and et...
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Machine Learning and Robot Perception - Bruno Apolloni et al (Eds) Part 7 pot
... consists of the robot going towards a goal which is a visual target. First of all, the robot moves the turret to center the target on the image and then the robot moves towards the target. In the ... robot , IEEE Journal of Robotics and Automation, RA-2(1), pp. 14–23, 1986. 168 G. Unal et al. Usage of this high level semantic information yields robust algorithms at a high...
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Machine Learning and Robot Perception - Bruno Apolloni et al (Eds) Part 10 potx
... α-shape of a finite point set S is a polytope uniquely determined by S and the param- eter α that controls the level-of-detail. A subset T ⊆ S of size |T | = k +1with 0 ≤ k ≤ 2 belongs to a set ... region-growing method, projection method, and sculpting-based method. In the next sub-sections we will ex- plain each of these categories. 6.4.1 Volumetric Methods The volumetric method consists...
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Machine Learning and Robot Perception - Bruno Apolloni et al (Eds) Part 12 potx
... of 3-D parameters from calibrated sets of 2-D parameters is computationally very efficient, requiring only a small fraction of computational power as compared to the low-level segmentation algorithms[5]. ... Motion Understanding the observation process is significantly non-trivial. Video images of the hu- man body are extremely high-dimensional signals and the mapping between body pose and...
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Machine Learning and Robot Perception - Bruno Apolloni et al (Eds) Part 3 pps
... objects, and applicability limits have been ex- plored. Potential application fields are industrial and mobile robotics, driv- ing aids and industrial tasks. Actually it isbeing used for topological ... 32 6-3 37. 10 Blaer, P., Allen, P. (2002) “Topological mobile robot localization us- ing fast vision techniques”. IEEE International Conference on Robot- ics and Automation, pp....
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Machine Learning and Robot Perception - Bruno Apolloni et al (Eds) Part 5 ppt
... inertial and visual mechanisms in the stabilization of gaze in natural and artificial systems, From: Motion Vision Computational, Neural, and Echological Con- straints, Eds. J. M. Zanker and ... human visual system : functional and topological transformation performed in the periferal visual field”, Biological Cyber- netics, vol. 44, 1982. 102 Y. Sun et al. model of the rob...
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Machine Learning and Robot Perception - Bruno Apolloni et al (Eds) Part 6 pdf
... discrete wavelet analysis will be used to decompose the raw signal into several signals with different bandwidths. This algorithm makes the signal, in this case, the raw angular velocity signal ... International Journal of Robotics Research, pages 36 6-3 81, vol.14, No.4, 1995. 4 Choi A (1997), Real-Time fundamental frequency estimation by least- square fitting, LIEEE Transactions on S...
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