@article {12545,
	title = {Object Detection, Tracking and Recognition for Multiple Smart Cameras},
	journal = {Proceedings of the IEEE},
	volume = {96},
	year = {2008},
	month = {2008/10//},
	pages = {1606 - 1624},
	abstract = {Video cameras are among the most commonly used sensors in a large number of applications, ranging from surveillance to smart rooms for videoconferencing. There is a need to develop algorithms for tasks such as detection, tracking, and recognition of objects, specifically using distributed networks of cameras. The projective nature of imaging sensors provides ample challenges for data association across cameras. We first discuss the nature of these challenges in the context of visual sensor networks. Then, we show how real-world constraints can be favorably exploited in order to tackle these challenges. Examples of real-world constraints are (a) the presence of a world plane, (b) the presence of a three-dimiensional scene model, (c) consistency of motion across cameras, and (d) color and texture properties. In this regard, the main focus of this paper is towards highlighting the efficient use of the geometric constraints induced by the imaging devices to derive distributed algorithms for target detection, tracking, and recognition. Our discussions are supported by several examples drawn from real applications. Lastly, we also describe several potential research problems that remain to be addressed.},
	keywords = {algorithm;geometric, analysis;image, association;distributed, camera;visual, cameras;, cameras;object, colour, constraints;imaging, data, detection;object, detection;sensor, detection;three-dimiensional, fusion;target, model;video, network;distributed, recognition;object, scene, sensor, sensor;multiple, sensors;geometry;image, sensors;object, smart, texture;intelligent, tracking;target, tracking;video},
	isbn = {0018-9219},
	doi = {10.1109/JPROC.2008.928758},
	author = {Sankaranarayanan,A. C and Veeraraghavan,A. and Chellapa, Rama}
}
@article {18007,
	title = {A bootstrapping model for directional wireless networks},
	journal = {Communications Letters, IEEE},
	volume = {10},
	year = {2006},
	month = {2006/12//},
	pages = {840 - 842},
	abstract = {Initially configuring or bootstrapping a connected topology in directional wireless networks is a challenging problem, especially when nodes only have local connectivity information and a limited number of transceivers. This paper presents a scalable bootstrapping model which integrates: 1) a distributed bottom-up algorithm that constructs a spanning tree with degree at most one larger than the optimal 2) a resource discovery algorithm for efficient dissemination of local connectivity information, and 3) synchronization protocols to guarantee the efficient emergence of overall network connectivity from local interactions. We investigate the feasibility and scalability of the proposed model. Results are presented for different network systems, with varying size and signaling data rates.},
	keywords = {(mathematics);, algorithm;resource, algorithm;spanning, bootstrapping, bottom-up, discovery, model;directional, network;distributed, networks;trees, protocols;protocols;radio, tree;synchronization, wireless},
	isbn = {1089-7798},
	doi = {10.1109/LCOMM.2006.060808},
	author = {Milner,S. and Llorca,J. and Anibha,A. and Vishkin, Uzi}
}
