Bayesian classification of shapes hidden in point cloud data

Srivastava, A.; Jermyn, I.H.

doi:10.1109/dsp.2009.4785949

Bayesian classification of shapes hidden in point cloud data

Srivastava, A.; Jermyn, I.H.

Authors

A. Srivastava

Professor Ian Jermyn i.h.jermyn@durham.ac.uk
Professor

Abstract

An interesting challenge in image processing is to classify shapes of polygons formed by selecting and ordering points in a 2D cluttered point cloud. This kind of data can result, for example, from a simple preprocessing of images containing objects with prominent boundaries. Taking an analysis-by-synthesis approach, we simulate high-probability configurations of sampled contours using models learnt from the training data to evaluate the given test data. To facilitate simulations, we develop statistical models for sources of (nuisance) variability: (i) shape variations of contours within classes, (ii) variability in sampling continuous curves into points, (iii) pose and scale variability, (iv) observation noise, and (v) points introduced by clutter. Finally, using a Monte Carlo approach, we estimate the posterior probabilities of different classes which leads to a Bayesian classification.

Citation

Srivastava, A., & Jermyn, I. (2009). Bayesian classification of shapes hidden in point cloud data. In IEEE 13th Digital Signal Processing Workshop and 5th IEEE Signal Processing Education Workshop, 2009 (DSP/SPE 2009) ; proceedings (359-364). https://doi.org/10.1109/dsp.2009.4785949

Conference Name	IEEE 13th Digital Signal Processing Workshop and 5th IEEE Signal Processing Education Workshop, 2009 (DSP/SPE 2009 )
Conference Location	Marco Island, USA
Publication Date	Jan 1, 2009
Deposit Date	Aug 12, 2011
Publicly Available Date	Apr 15, 2016
Publisher	Institute of Electrical and Electronics Engineers
Pages	359-364
Book Title	IEEE 13th Digital Signal Processing Workshop and 5th IEEE Signal Processing Education Workshop, 2009 (DSP/SPE 2009) ; proceedings
DOI	https://doi.org/10.1109/dsp.2009.4785949

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