Danijel Maricic

dblp:56/9233 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2010
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Graphics, computer vision, multimedia, augmented reality and games · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer networks
1 paper
Internet of things and sensor networks · 50% Physical-layer communications · 50%
Computer graphics and multimedia
1 paper
Image and video coding · 67% Computational photography and imaging · 33%

Topics — the 5 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Physical-layer communications
power allocation
0.112010
Adaptive Sensing and Optimal Power Allocation for Wireless Video Sensors With Sigma-Delta Imager · IEEE Trans. Image Process. 2010
Internet of things and sensor networks › camera sensor networks
wireless video sensor networks
0.112010
Adaptive Sensing and Optimal Power Allocation for Wireless Video Sensors With Sigma-Delta Imager · IEEE Trans. Image Process. 2010
Computational photography and imaging › image sensor
image sensor design
0.012010
Adaptive Sensing and Optimal Power Allocation for Wireless Video Sensors With Sigma-Delta Imager · IEEE Trans. Image Process. 2010
Image and video coding
rate-distortion optimization
0.012010
Adaptive Sensing and Optimal Power Allocation for Wireless Video Sensors With Sigma-Delta Imager · IEEE Trans. Image Process. 2010
Image and video coding
video compression
0.012010
Adaptive Sensing and Optimal Power Allocation for Wireless Video Sensors With Sigma-Delta Imager · IEEE Trans. Image Process. 2010

Methods — techniques the papers use, named apart from their topics

power-rate-distortion optimization · 0.2adaptive sensing · 0.2
YearPublicationVenuePosition
2010 Adaptive Sensing and Optimal Power Allocation for Wireless Video Sensors With Sigma-Delta Imager
abstract
We consider optimal power allocation for wireless video sensors (WVSs), including the image sensor subsystem in the system analysis. By assigning a power-rate-distortion (P-R-D) characteristic for the image sensor, we build a comprehensive P-R-D optimization framework for WVSs. For a WVS node operating under a power budget, we propose power allocation among the image sensor, compression, and transmission modules, in order to minimize the distortion of the video reconstructed at the receiver. To demonstrate the proposed optimization method, we establish a P-R-D model for an image sensor based upon a pixel level sigma-delta (Σ∆) image sensor design that allows investigation of the tradeoff between the bit depth of the captured images and spatio-temporal characteristics of the video sequence under the power constraint. The optimization results obtained in this setting confirm that including the image sensor in the system optimization procedure can improve the overall video quality under power constraint and prolong the lifetime of the WVSs. In particular, when the available power budget for a WVS node falls below a threshold, adaptive sensing becomes necessary to ensure that the node communicates useful information about the video content while meeting its power budget.
Malisa Marijan, Ilker Demirkol, Danijel Maricic, Gaurav Sharma 0001, Zeljko Ignjatovic
IEEE Trans. Image Process.3