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--- projects [2013/04/29 12:26] – mb
+++ projects [2013/08/09 20:55] – pd
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-====== Available Projects  ======
+====== Proposed Projects  ======
-Currently offered Projects, Summer 2013
+Current proposed Projects, Fall 2013
-(some projects still subject to confirmation)
+Current possible  projects will be listed here at end of August.
+------------------
+\\
+\\
+=====Previous Projects from Summer 2013=====
 ======Tracking and Activity Recognition Through Consensus in Distributed Camera Networks======
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 **Required Background: ** Computer Vision or Signal and Systems Course preferred; Matlab; Interest in Signal/Image Processing
-Short Description: Over the past decade, large-scale camera networks have become increasingly popular in a wide range of applications, including: (i) Sports analysis; (ii) Security and surveillance; (iii) disaster response, and; (iv) Environmental modeling, where the objective is to follow the trajectory of a key target, for example, a star player in a soccer game or a suspect in a surveillance environment. In many applications, bandwidth constraints, security concerns, and difficulty in storing and analyzing large amounts of image data centrally at a single location necessitate the development of distributed camera network architectures. In this project, we investigate distributed scene analysis algorithms, where each camera estimates certain parameters of the target using a signal processing algorithm based upon its own set of observations. The local estimates are then shared with the neighboring cameras in an iterative, goosip-type fashion, and a final estimate is computed across the network using consensus algorithms. The selected student will develop Matlab code to apply distributed signal processing algorithms [1,2] that have been developed in the Signal Processing and Communications lab for target tracking and activity recognition in distributed camera networks.
+**Short Description: **Over the past decade, large-scale camera networks have become increasingly popular in a wide range of applications, including: (i) Sports analysis; (ii) Security and surveillance; (iii) disaster response, and; (iv) Environmental modeling, where the objective is to follow the trajectory of a key target, for example, a star player in a soccer game or a suspect in a surveillance environment. In many applications, bandwidth constraints, security concerns, and difficulty in storing and analyzing large amounts of image data centrally at a single location necessitate the development of distributed camera network architectures. In this project, we investigate distributed scene analysis algorithms, where each camera estimates certain parameters of the target using a signal processing algorithm based upon its own set of observations. The local estimates are then shared with the neighboring cameras in an iterative, goosip-type fashion, and a final estimate is computed across the network using consensus algorithms. The selected student will develop Matlab code to apply distributed signal processing algorithms [1,2] that have been developed in the Signal Processing and Communications lab for target tracking and activity recognition in distributed camera networks.