NDLI: Online control of active camera networks for computer vision tasks

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ACM Transactions on Sensor Networks (TOSN) : Volume 13

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Socio-economic vision graph generation and handover in distributed smart camera networks

Progressively refined wyner-ziv video coding for visual sensors

A predictive duty cycle adaptation framework using augmented sensing for wireless camera networks

Camera selection for tracking in distributed smart camera networks

Low-complexity scalable distributed multicamera tracking of humans

Online control of active camera networks for computer vision tasks

Calibrating a wide-area camera network with non-overlapping views using mobile devices

Multicamera video summarization and anomaly detection from activity motifs

Adaptive instantiation of the protocol interference model in wireless networked sensing and control

Optimal nonuniform deployment of sensors for distributed detection in wireless sensor networks

Maximum likelihood analysis of conflicting observations in social sensing

Troubleshooting interactive complexity bugs in wireless sensor networks using data mining techniques

Radio diversity for reliable communication in sensor networks

Coverage quality and smoothness criteria for online view selection in a multi-camera network

On detection and tracking of variant phenomena clouds

Failure detection in wireless sensor networks: A sequence-based dynamic approach

Analysis of a prioritized contention model for multimedia wireless sensor networks

Data-driven link quality prediction using link features

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ACM Transactions on Sensor Networks (TOSN) : Volume 1

Online control of active camera networks for computer vision tasks

Content Provider	ACM Digital Library
Author	Welch, Greg Ilie, Adrian
Copyright Year	2014
Abstract	Large networks of cameras have been increasingly employed to capture dynamic events for tasks such as surveillance and training. When using active cameras to capture events distributed throughout a large area, human control becomes impractical and unreliable. This has led to the development of automated approaches for online camera control. We introduce a new automated camera control approach that consists of a stochastic performance metric and a constrained optimization method. The metric quantifies the uncertainty in the state of multiple points on each target. It uses state-space methods with stochastic models of target dynamics and camera measurements. It can account for occlusions, accommodate requirements specific to the algorithms used to process the images, and incorporate other factors that can affect their results. The optimization explores the space of camera configurations over time under constraints associated with the cameras, the predicted target trajectories, and the image processing algorithms. The approach can be applied to conventional surveillance tasks (e.g., tracking or face recognition), as well as tasks employing more complex computer vision methods (e.g., markerless motion capture or 3D reconstruction).
Starting Page	1
Ending Page	40
Page Count	40
File Format	PDF
ISSN	15504859
e-ISSN	15504867
DOI	10.1145/2530283
Volume Number	10
Issue Number	2
Journal	ACM Transactions on Sensor Networks (TOSN)
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2014-01-31
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	3D reconstruction Camera control Active camera networks Computer vision Motion capture Surveillance
Content Type	Text
Resource Type	Article
Subject	Computer Networks and Communications

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

On-line control of active camera networks for computer vision tasks

Online control of active camera networks for computer vision tasks.

Garment-based motion capture (GaMoCap): high-density capture of human shape in motion

On-line control of active camera networks for computer vision tasks.

Multi-Camera Coordination and Control in Surveillance Systems: A Survey

Motion reconstruction using sparse accelerometer data

Tracking the articulated motion of the human body with two RGBD cameras

An adaptive focus-of-attention model for video surveillance and monitoring

Accurate realtime full-body motion capture using a single depth camera

Online control of active camera networks for computer vision tasks

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