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Copyright © IPRS Project Novelty Detection and 3D Shape Retrieval Paulo Drews Jr

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Copyright © IPRS Project March, Gaussian Mixture Model Shape Retrieval (Mathematical Space of GMM) CARMEN Integration / Experiment Change Detection Algorithm

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Steps of the work 1 – Gaussian Mixture Models Implemented in C/C++ based in Cluster Library from Charles A. Bouman (Purdue University) Automatically compute the number of GMM Speedup but it isnt realtime with a lot of points (>5000) yet. Look for a method to reduce the number of points (size of the grid in occupancy grid) Generate more than one GMM to one “shape”, solve it with a prior knowledge.

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Steps of the work 2 – Change Detection Implemented in C/C++ using EMD library from Carlo Tomasi (Duke University) Works fine using a greedy algorithm (Fast) Possible implements something to detect false positive

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Steps of the work 3- Shape Retrievel Implemented in C/C++ based in the library levmar from Manolis Lourakis (Foundation for Research and Technology – Hellas) Hard to solve underdetermined problem, 6 variables but only 3 equation(using 3 eigenvalues). Need a bayes classifier ? Problem to compute the eigenvalue of non- symmetric matrix (generalized eigenvalue) – Look for a new library

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Steps of the work 3- Shape Retrievel Instead of using basic shapes(plane,sphere), using a superquadrics less than 1: a pointy octahedron with concave faces and sharp edges. exactly 1: a regular octahedron. between 1 and 2: an octahedron with convex faces, blunt edges and blunt corners. exactly 2: a sphere greater than 2: a cube with rounded edges and corners. infinite (in the limit): a cube

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Steps of the work 4- Integration with Carmen/Tests Meeting with João Monteiro to define details. Start with 2D maps and Change Detection After implemented the 3D maps, try put the shape retrievel in Carmen.

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Some tests Real Data Old Data – The Door (2160 points) New Data – The Corridor with the door (40000 points) Uknown the Number Classer – 20 Class the maximun size Time Processing – 118 s

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Some tests 2- Simulated data Old Data – Corridor (1323 points) New Data - Corridor + Desk + Ball (2960 points) Time processing – without knowledge 3.8 s / with knowledge 3 s

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Copyright © IPRS Project End

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