DocumentCode :
295897
Title :
Strategies for visual navigation, target detection and camouflage: inspirations from insect vision
Author :
Srinivasan, M.V.
Author_Institution :
Centre for Visual Sci., Australian Nat. Univ., Canberra, ACT, Australia
Volume :
5
fYear :
1995
fDate :
Nov/Dec 1995
Firstpage :
2456
Abstract :
Recent research, observing freely flying insects reveals a number of computational “short cuts” that insects use for perceiving their visual world in three dimensions, and navigating successfully in it. Bees segment objects from their backgrounds by sensing the apparent relative motion at the boundary between object and background. The distances to objects are gauged in terms of the apparent speeds of motion of the objects´ images, rather than by using complex stereo mechanisms to compute range. Hoverflies “shadow” conspecific by camouflaging their motion. The shadowing insect achieves this by moving in such a way as to emulate the motion of the image of a stationary object in the eye of the moving shadowy. Bees flying through a tunnel maintain equidistance to the side walls by balancing the apparent speeds of the images of the walls. Bees landing on a horizontal surface hold constant the image velocity of the surface as they approach it, thus automatically ensuring that flight speed is close to zero at touchdown. Applications of some these strategies to robot navigation and machine vision are discussed
Keywords :
biocybernetics; biology; computer vision; motion estimation; navigation; object recognition; vision; image motion; insect vision; machine vision; motion camouflage; robot navigation; target detection; visual navigation; Australia; Eyes; Image segmentation; Insects; Machine vision; Navigation; Object detection; Optical refraction; Robot vision systems; Shadow mapping;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 1995. Proceedings., IEEE International Conference on
Conference_Location :
Perth, WA
Print_ISBN :
0-7803-2768-3
Type :
conf
DOI :
10.1109/ICNN.1995.487747
Filename :
487747
Link To Document :
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