Paper Info
Title
Real-Time Image Content Assessment for Underwater Robot Manoeuvring Based on Structural Tensor Analysis.
Abstract
The paper presents an efficient method for real-time image analysis for manoeuvring of the underwater robot. Image analysis is done after computing the structural tensor components which unveil rich texture and texture-less areas. To allow a power efficient underwater operation in real-time the method is implemented on the Jetson TK1 self-standing graphics card using the CUDA compute architecture. The laboratory experimental results show that the system is capable of processing about 40 Full HD images per second while allowing orientation toward texture specific regions for obstacle avoidance.
Year
DOI
Venue
2017
10.1007/978-3-319-59162-9_48
PROCEEDINGS OF THE 10TH INTERNATIONAL CONFERENCE ON COMPUTER RECOGNITION SYSTEMS CORES 2017
Keywords
Field
DocType
Robot manoeuvring,Structural tensor,Underwater operation,CUDA,Real-time programming
Obstacle avoidance,Graphics,Computer vision,Power efficient,Tensor,Computer science,CUDA,Image content,Underwater robot,Artificial intelligence,Underwater
Conference
Volume
ISSN
Citations 
578
2194-5357
0
PageRank 
References 
Authors
0.34
3
2
Name
Order
Citations
PageRank
Jakub Nawala101.35
Boguslaw Cyganek214524.53