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Academic Press Library in Signal Processing by Sergios Theodoridis

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Chapter 10

Multi-Path Marginal Space Learning for Object Detection

Adrian Barbu,    Department of Statistics, Florida State University, Tallahassee, FL, USA,    abarbu@stat.fsu.edu

Abstract

This chapter introduces a novel method for fast detection of objects with a large number of parameters. The method is based on Marginal Space Learning (MSL), which is a learning-based optimization technique that approaches the search for objects in images as a particle filter in a chain of subspaces of increasing dimensions, using trained detectors to prune the particles in the subspaces. MSL has been used extensively in Medical Imaging for detecting organs and landmarks in 2D and 3D data and for detecting and tracking curve-like structures such as guidewires ...

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