Title :
Experiments on depth from magnification and blurring
Author :
Ahn, Sang Chul ; Lee, Sukhan ; Meyyappan, Ashok ; Schenker, Paul
Author_Institution :
Dept. of Electr. Eng. Syst., Univ. of Southern California, Los Angeles, CA, USA
Abstract :
A new method of extracting depth from blurring and magnification of objects or local scene is presented. Assuming no active illumination, the images are taken at two camera positions of a small displacement, using a single standard camera with telecentric lens. Thus, the depth extraction method is simple in structure and efficient in computation. Fusing the two disparate sources of depth information, magnification and blurring, the proposed method provides more accurate and robust depth estimation. This paper describes the process of various experimentations performed to validate this concept and describes the present work that has been done in that field. The experimental result shows less than 1% error for an optimal depth range. The ultimate aim of this concept would be the construction of dense 3D maps of objects and real time continuous estimation of depth
Keywords :
computer vision; feature extraction; sensor fusion; blurring; computer vision; data fusion; depth estimation; depth extraction; magnification; telecentric lens; Apertures; Cameras; Costs; Focusing; Laboratories; Laser radar; Lenses; Propulsion; Robot motion; Robot vision systems;
Conference_Titel :
Intelligent Robots and Systems, 1997. IROS '97., Proceedings of the 1997 IEEE/RSJ International Conference on
Conference_Location :
Grenoble
Print_ISBN :
0-7803-4119-8
DOI :
10.1109/IROS.1997.655092