Machine Learning and Robot Perception - Bruno Apolloni et al (Eds) Part 5 ppt
... Panerai and F.A. Miles, “The role of inertial and visual mechanisms in the stabilization of gaze in natural and artificial systems, From: Motion Vision Computational, Neural, and Echological Con- straints, ... 8(4), 1990. 53 . C. Busetti, F.A. Miles and R.J. Krauzlis, “Radial optical flow induces vergence eye movements at ultra-short latencies”, nature, vol. 390, pp. 51 2 51 5...
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... 194 G. Unal et al. Fig. 5. 15. A walking person (Frames shown L-R-top-bottom) is tracked by the polygonal tracker 180 G. Unal et al. Fig. 5. 5. Two rays-swimming video noisy version ... outward unit normal of edge (P kí1 í P k) (resp. (P k í P k+1)), and L parameterizes a line between P kí1 and P k or P k and P k+1. We note the similarity between this polygonal evolution e...
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... 8 12 15 20 0 93 91 ,5 87 ,5 84 71 29 15 90 88 ,5 86 78 63 18 ,5 30 86 84 79 ,5 73 45, 5 11 ,5 45 82 78 ,5 73 ,5 60 25, 5 0 60 77 72 56 ,5 32 12 ,5 0 75 65, 5 52 ,5 37 16 0 0 1.6.1 Robot Localization ... 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 o...
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Machine Learning and Robot Perception - Bruno Apolloni et al (Eds) Part 3 pps
... 3, pp. 342 5- 3 0. 4 Balkenius, C. (1998) "Spatial learning with perceptually grounded rep- resentations". Robotics and Autonomous Systems, vol. 25, pp. 16 5- 1 75. 5 Barber R., Salichs, ... at the point Z if it is analytic at point z and its derivative at z is non-zero. 1 Learning Visual Landmarks for Mobile Robot Topological Navigation 55 55 Yuille, A., Halliman...
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Machine Learning and Robot Perception - Bruno Apolloni et al (Eds) Part 4 potx
... 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, ... visual work space and finally, (5) the cost, size and performance 6 of the sensor. To develop a space-variant vision sensor, several attempts to combine peripheral and fov...
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Machine Learning and Robot Perception - Bruno Apolloni et al (Eds) Part 6 pdf
... estimate. 0 5 10 15 20 25 30 0 0 .5 1 1 .5 2 Time Length Estimate 0 5 10 15 20 25 30 0 0.2 0.4 0.6 0.8 1 Time p 0 5 10 15 20 25 30 0 0 .5 1 1 .5 2 Time Length Estimate 0 5 10 15 20 25 30 0 0.2 0.4 0.6 0.8 1 Time ... M=45kg 0 5 10 15 20 25 0 10 20 30 40 50 60 70 Time(s) mass(kg) Fig. 3.7. Mass Estimation, for m = 55 kg 3. On-line Model Learning for Mo...
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Machine Learning and Robot Perception - Bruno Apolloni et al (Eds) Part 7 pot
... input and output spaces and with real continuous reinforcement signal. 4 .5. 1 Neural Network Architecture The neural network architecture proposed to implement the reinforcement learning algorithm ... and Autonomous Systems, vol. 38, no. 3-4 , pp. 137–148, 2002. 8 Z. Kalmar, C. Szepesvari, and A. Lorincz, “Module-based reinforcement learning: Experiments with a real robot...
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Machine Learning and Robot Perception - Bruno Apolloni et al (Eds) Part 9 doc
... 12–49, 1988. 45. D. Peng, B. Merriman, S. Osher, H-K. Zhao, and M. Kang, “A PDE- based fast local level set method,” J. Computational Physics, vol. 255 , pp. 410–438, 1999. 46. T.F. Chan and L.A. ... Fig. 5. 19. A clownfish with its textured body swims in its host anemone (Frames 1, 13, 39 ,59 , 64, 67, 71, 74, 78, 81, 85, 95, 1 05, 120, 150 , 155 are shown left-right top-bottom)....
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Machine Learning and Robot Perception - Bruno Apolloni et al (Eds) Part 10 potx
... Range and Intensity Images 237 5 01234 6789 10 11 12 13 14 (a) (c) (d) (b) (e) −0.8 +0. 15 −0.8 +0. 15 +0. 45 +0. 85 +0.3 +0.3 −0. 65 −0. 65 −1 .5 −1 .5 +0. 45 +0. 85 −0.3 −0.3 +0.7 +0.7 6.4.4 Projection Methods The ... 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...
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