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S. Asaad

dblp:126/4886 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 1996
—ORCID · none

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

Artificial intelligence and machine learning · 1 · 1 first-authorSystems, architecture and hardware · 1 · 1 first-author

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.

Artificial intelligence
1 paper
Robot navigation and mapping · 50% Video understanding and tracking · 50%
Computer architecture, parallel and distributed computing, and storage systems
1 paper
Embedded and real-time systems · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Robot navigation and mapping
active vision		 0.011996
A low-cost, DSP-based, intelligent vision system for robotic applications · ICRA 1996
Computer vision › Video understanding and tracking
object tracking		 0.011996
A low-cost, DSP-based, intelligent vision system for robotic applications · ICRA 1996
Embedded and real-time systems › real-time embedded systems › multimedia embedded systems
embedded vision system		 0.011996
A low-cost, DSP-based, intelligent vision system for robotic applications · ICRA 1996

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

edge-based object tracking · 0.0DSP implementation · 0.0
YearPublicationVenuePosition
1996 A low-cost, DSP-based, intelligent vision system for robotic applications
abstract
In this paper we present the design and implementation of a novel low-cost active vision system for robotic applications. The system is comprised of two parts: A 4-DOF trinocular active camera head and a DSP-based image acquisition and processing board. Design issues and tradeoffs are discussed. The performance of the system is evaluated by running an edge-based object tracking algorithm that is also presented in this paper. Experimental results show that the system is capable of tracking objects at 30 frames/sec.
S. Asaad, Magued Bishay, D. Mitchell Wilkes, Kazuhiko Kawamura
 ICRA1