Motion projection for floating object detection

Authors:
Zhao-Yi Wei;Dah-Jye Lee;David Jilk;Robert Schoenberger
Affiliations:
Dept. of Electrical and Computer Eng., Brigham Young University, Provo, UT;Dept. of Electrical and Computer Eng., Brigham Young University, Provo, UT;eCortex, Inc., Boulder, CO;Symmetron, LLC, A division of ManTech International Corp., Fairfax, VA
Venue:
ISVC'07 Proceedings of the 3rd international conference on Advances in visual computing - Volume Part II
Year:
2007

Citing 2
Cited 1

A Noniterative Greedy Algorithm for Multiframe Point Correspondence

IEEE Transactions on Pattern Analysis and Machine Intelligence
Survey on Block Matching Motion Estimation Algorithms and Architectures with New Results

Journal of VLSI Signal Processing Systems

An evaluation of pixel-based methods for the detection of floating objects on the sea surface

EURASIP Journal on Advances in Signal Processing - Special issue on advances in signal processing for maritime applications

Quantified Score

Hi-index	0.01

Visualization

Abstract

Floating mines are a significant threat to the safety of ships in theatres of military or terrorist conflict. Automating mine detection is difficult, due to the unpredictable environment and high requirements for robustness and accuracy. In this paper, a floating mine detection algorithm using motion analysis methods is proposed. The algorithm aims to locate suspicious regions in the scene using contrast and motion information, specifically regions that exhibit certain predefined motion patterns. Throughput of the algorithm is improved with a parallel pipelined data flow. Moreover, this data flow enables further computational performance improvements though special hardware such as field programmable gate arrays (FPGA) or Graphics Processing Units (GPUs). Experimental results show that this algorithm is able to detect mine regions in the video with reasonable false positive and minimum false negative rates.