@booklet {19456,
	title = {Making infrastructure visible: a case study of home networking},
	year = {2011},
	month = {2011/06/24/},
	abstract = {In this dissertation, I examine how making infrastructure visible affects users{\textquoteright} engagement with that infrastructure, through the case study of home networking. I present empirical evidence of the visibility issues that home networks present to users and how these results informed the design of a prototype called Kermit to visualize aspects of the home network. Through my implementation and evaluation of Kermit, I derive implications for making infrastructure visible in ways that enable end-users to manage and understand the systems they use everyday. I conclude with suggestions for future work for making home networks, and infrastructure more generally, more visible.},
	keywords = {Home computer networks, home networking, Human computer interaction, Human-computer interaction, infrastructure, Inspectability, Local area networks (Computer networks), visibility},
	doi = {Dissertation},
	url = {https://smartech.gatech.edu/handle/1853/41152},
	author = {Marshini Chetty}
}
@conference {13245,
	title = {Scalable image-based multi-camera visual surveillance system},
	booktitle = {Proceedings. IEEE Conference on Advanced Video and Signal Based Surveillance, 2003.},
	year = {2003},
	month = {2003/07//},
	pages = {205 - 212},
	abstract = {We describe the design of a scalable and wide coverage visual surveillance system. Scalability (the ability to add and remove cameras easily during system operation with minimal overhead and system degradation) is achieved by utilizing only image-based information for camera control. We show that when a pan-tilt-zoom camera pans and tilts, a given image point moves in a circular and a linear trajectory, respectively. We create a scene model using a plan view of the scene. The scene model makes it easy for us to handle occlusion prediction and schedule video acquisition tasks subject to visibility constraints. We describe a maximum weight matching algorithm to assign cameras to tasks that meet the visibility constraints. The system is illustrated both through simulations and real video from a 6-camera configuration.},
	keywords = {ACQUISITION, algorithm;, camera;, constraints;, feature, hidden, image-based, MATCHING, maximum, multi-camera, occlusion, pan-tilt-zoom, PLAN, prediction;, processing;, removal;, scalable, scheduling;, signal, Surveillance, surveillance;, system;, task, video, view;, visibility, visual, weight},
	doi = {10.1109/AVSS.2003.1217923},
	author = {Lim,Ser-Nam and Davis, Larry S. and Elgammal,A.}
}
