2A2-J05 Removal of Scene Occluders and 3D Measurement of Objects in Underwater Images Acquired with High Speed Stereo Camera(Robot Vision(1))

2012 ◽  
Vol 2012 (0) ◽  
pp. _2A2-J05_1-_2A2-J05_4
Author(s):  
Masato HARATA ◽  
Atsushi YAMASHITA ◽  
Toru KANEKO ◽  
Hajime ASAMA
Keyword(s):  
High Speed ◽  
Robot Vision ◽  
3D Measurement ◽  
Stereo Camera

3D Measurement of a Moving Object Using a Moving Camera Attached with a 6-Axis Sensor

2014 ◽  
Vol 18 (5) ◽  
pp. 736-744
Author(s):  
Toshihiro Akamatsu ◽  
◽  
Fangyan Dong ◽  
Kaoru Hirota
Keyword(s):  
Mobile Robots ◽  
Computational Cost ◽  
Moving Object ◽  
Computational Time ◽  
3D Measurement ◽  
Moving Camera ◽  
Stereo Camera ◽  
Continuous Frame

Measurement using a moving camera and a 6-axis sensor under the camera is proposed to determine the distance from the camera to the surface of a moving object and the object’s position movement in two continuous frame images. This makes it possible to measure the 3D position of a moving object at half of the computational cost while keeping the same accuracy as using a stereo camera. 3D measurement experiments with several original images show that the computational time using the proposal is about twice as fast as that of a stereo camera. The proposed method is planning to be used to vehicles or mobile robots avoid obstacles, and its use as a depth meter is also investigated.

Still Corresponding Points Extraction Using a Moving Monocular Camera with a Motion Sensor

2015 ◽  
Vol 19 (2) ◽  
pp. 319-329
Author(s):  
Toshihiro Akamatsu ◽  
◽  
Fangyan Dong ◽  
Kaoru Hirota
Keyword(s):  
Computer Graphics ◽  
Mobile Robot ◽  
Moving Objects ◽  
Robot Vision ◽  
Motion Sensor ◽  
3D Measurement ◽  
Sensor Noise ◽  
Monocular Camera ◽  
Mobile Robot Vision ◽  
Extraction Experiment

The method of extracting still corresponding points proposed in this paper uses a moving monocular camera connected to a 6-axis motion sensor. It classifies corresponding points between two consecutive frames containing still/moving objects and chooses corresponding points appropriate for 3D measurement. Experiments are done extracting still corresponding points with 2 scenes from original computer graphics images. Results for scene 1 show that accuracy is 0.98, precision 0.96, and recall 1.00. Robustness against sensor noise is confirmed. Extraction experiment results with real scenes show that accuracy is 0.86, precision 0.88, and recall 0.94. We plan to include the proposed method in 3D measurement with real images containing still/moving objects and to apply it to obstacles avoidance for vehicles and to mobile robot vision systems.

2A1-L09 High speed stereo vision emulating the visual cortex(Robot Vision)

2011 ◽  
Vol 2011 (0) ◽  
pp. _2A1-L09_1-_2A1-L09_2
Author(s):  
Yukihiro YOKOYAMA ◽  
Tadashi SANADA ◽  
Hirotsugu OKUNO ◽  
Tetsuya YAGI
Keyword(s):  
Visual Cortex ◽  
Stereo Vision ◽  
High Speed ◽  
Robot Vision
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