Download book Robust Target Localization and Segmentation
Download book Robust Target Localization and Segmentation
Robust Target Localization and Segmentation.cOmar Arif
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Author: Omar Arif
Page Count: 116 pages
Published Date: 12 Sep 2010
Publisher: LAP Lambert Academic Publishing
Publication Country: Germany
Language: English
ISBN: 9783843350389
File Name: Robust.Target.Localization.and.Segmentation.pdf
Download Link: Robust Target Localization and Segmentation
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This work aims to contribute to the area of visual tracking, which is the process of identifying an object of interest through a sequence of successive images. The thesis explores kernel-based statistical methods. Two algorithms are developed for visual tracking that are robust to noise and occlusions. In the first algorithm, a kernel PCA-based eigenspace representation is used. The de-noising and clustering capabilities of the kernel PCA procedure lead to a robust algorithm. In the second method, a robust density comparison framework is developed that is applied to visual tracking, where an object is tracked by minimizing the distance between a model distribution and given candidate distributions. The superior performance of kernel-based algorithms comes at a price of increased storage and computational requirements. A novel method is developed that takes advantage of the universal approximation capabilities of generalized radial basis function neural networks to reduce the computational and storage requirements for kernel-based methods.
Read online Robust Target Localization and Segmentation Buy Robust Target Localization and Segmentation Download and read Robust Target Localization and Segmentation for pc, mac, kindle, readers Download to iPad/iPhone/iOS, B&N nook Robust Target Localization and Segmentation
Robust Target Localization and Segmentation.cOmar Arif
Author: Omar Arif
Page Count: 116 pages
Published Date: 12 Sep 2010
Publisher: LAP Lambert Academic Publishing
Publication Country: Germany
Language: English
ISBN: 9783843350389
File Name: Robust.Target.Localization.and.Segmentation.pdf
Download Link: Robust Target Localization and Segmentation
---------------------------------------------------------------
This work aims to contribute to the area of visual tracking, which is the process of identifying an object of interest through a sequence of successive images. The thesis explores kernel-based statistical methods. Two algorithms are developed for visual tracking that are robust to noise and occlusions. In the first algorithm, a kernel PCA-based eigenspace representation is used. The de-noising and clustering capabilities of the kernel PCA procedure lead to a robust algorithm. In the second method, a robust density comparison framework is developed that is applied to visual tracking, where an object is tracked by minimizing the distance between a model distribution and given candidate distributions. The superior performance of kernel-based algorithms comes at a price of increased storage and computational requirements. A novel method is developed that takes advantage of the universal approximation capabilities of generalized radial basis function neural networks to reduce the computational and storage requirements for kernel-based methods.
Read online Robust Target Localization and Segmentation Buy Robust Target Localization and Segmentation Download and read Robust Target Localization and Segmentation for pc, mac, kindle, readers Download to iPad/iPhone/iOS, B&N nook Robust Target Localization and Segmentation