Title
Real-time motion detection based on SW/HW-codesign for walking rescue robots
Abstract
In a rescue operation walking robots offer a great deal of flexibility in traversing uneven terrain in an uncontrolled environment. For such a rescue robot, each motion is a potential vital sign and the robot should be sensitive enough to detect such motion, at the same time maintaining high accuracy to avoid false alarms. However, the existing techniques for motion detection have severe limitations in dealing with strong levels of ego-motion on walking robots. This paper proposes an optical flow-based method for the detection of moving objects using a single camera mounted on a hexapod robot. The proposed algorithm estimates and compensates ego-motion to allow for object detection from a continuously moving robot, using a first-order-flow motion model. Our algorithm can deal with strong rotation and translation in 3D, with four degrees of freedom. Two alternative object detection methods using a 2D-histogram based vector clustering and motion-compensated frame differencing, respectively, are examined for the detection of slow- and fast-moving objects. The FPGA implementation with optimized resource utilization using SW/HW codesign can process video frames in real-time at 31 fps. The new algorithm offers a significant improvement in performance over the state-of-the-art, under harsh environment and performs equally well under smooth motion.
Year
DOI
Venue
2013
10.1007/s11554-011-0239-0
Journal of Real-time Image Processing
Keywords
Field
DocType
alternative object detection method,first-order-flow motion model,smooth motion,fast-moving object,object detection,rescue robot,motion detection,new algorithm,hexapod robot,real-time motion detection,proposed algorithm estimate,Embedded systems,FPGA-based real-time processing,Software/hardware codesign,Optical flow,Egomotion estimation,Moving object detection
Computer vision,Object detection,Motion detection,Computer science,Rescue robot,Field-programmable gate array,Real-time computing,Artificial intelligence,Cluster analysis,Robot,Hexapod,Optical flow
Journal
Volume
Issue
ISSN
8
4
1861-8200
Citations 
PageRank 
References 
1
0.36
14
Authors
6
Name
Order
Citations
PageRank
Johny Paul1133.98
Andreas Laika2166.22
Christopher Claus322120.39
Walter Stechele436552.77
Adam El Sayed Auf5152.38
Erik Maehle6676130.34