Title

Applications Of Compressive Sensing To Surveillance Problems

Abstract

In many surveillance scenarios, one concern that arises is how to construct an imager that is capable of capturing the scene with high fidelity. This could be problematic for two reasons: First, the optics and electronics in the camera may have difficulty in dealing with so much information; second, bandwidth constraints may pose difficulty in transmitting information from the imager to the user efficiently for reconstruction or realization. This paper is a study of the application of various compressive sensing methods to surveillance problems. It is based largely on the work of [7], with theory and algorithms presented in the same manner. We explore two of the seminal works in compressive sensing and present the key theorems and definitions from these two papers. We then survey three different surveillance scenarios and their respective compressive sensing solutions. The original contribution of this paper is the development of a distributed compressive sensing model. © Springer India 2014.

Publication Date

1-1-2014

Publication Title

Springer Proceedings in Mathematics and Statistics

Volume

91

Number of Pages

121-150

Document Type

Article; Proceedings Paper

Personal Identifier

scopus

DOI Link

https://doi.org/10.1007/978-81-322-1952-1_9

Socpus ID

84906834048 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/84906834048

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