Determining Vision Graphs for Distributed Camera Networks Using Feature Digests
نویسندگان
چکیده
منابع مشابه
Determining Vision Graphs for Distributed Camera Networks Using Feature Digests
We propose a decentralized method for obtaining the vision graph for a distributed, ad-hoc camera network, in which each edge of the graph represents two cameras that image a sufficiently large part of the same environment. Each camera encodes a spatially well-distributed set of distinctive, approximately viewpoint-invariant feature points into a fixed-length “feature digest” that is broadcast ...
متن کاملDetermining Vision Graphs for Camera Networks Using Feature Digests
We define and discuss how to obtain the vision graph for a distributed camera network, in which cameras and processing nodes may be spread over a wide geographical area, with no centralized processor and limited ability to communicate a large amount of information over long distances. In the vision graph, each camera is represented by a node, and an edge appears between two nodes if the two cam...
متن کاملCalibrating Distributed Camera Networks Using Belief Propagation
We discuss how to obtain the accurate and globally consistent self-calibration of a distributed camera network, in which camera nodes with no centralized processor may be spread over a wide geographical area. We present a distributed calibration algorithm based on belief propagation, in which each camera node communicates only with its neighbors that image a sufficient number of scene points. T...
متن کاملCAMGRAPH: Distributed Graph Processing for Camera Networks
With the proliferation of sensors of various kinds, especially cameras, large-scale situation awareness applications employing camera networks will become common place. These applications are inherently distributed, dynamic, interactive, run 24×7, and generate spatiotemporal events that need to be stored and retrieved in a timely manner to satisfy real-time constraints. To address these challen...
متن کاملDistributed Probabilistic Learning for Camera Networks
Probabilistic approaches to computer vision typically assume a centralized setting, with the algorithm granted access to all observed data points. However, many problems in wide-area surveillance can benefit from distributed modeling, either because of physical or computations constraints. In this work we present an approach to estimation and learning of generative probabilistic models in a dis...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: EURASIP Journal on Advances in Signal Processing
سال: 2006
ISSN: 1687-6180
DOI: 10.1155/2007/57034