Characterisation of variable focus liquid lens camera system for depth estimation of a moving object
Depth estimation of an object or a scene are used for the purpose of motion detection, obstacle detection, positioning, depth mapping, or 3D shape recovery. These capabilities can be applied in home, industry, medical, education and other areas of applications. There are different types of dep...
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| Format: | Thesis |
| Language: | English English English |
| Published: |
2021
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| Subjects: | |
| Online Access: | http://eprints.uthm.edu.my/4006/1/24p%20ADRIAN%20SOON%20BEE%20TIONG.pdf http://eprints.uthm.edu.my/4006/2/ADRIAN%20SOON%20BEE%20TIONG%20COPYRIGHT%20DECLARATION.pdf http://eprints.uthm.edu.my/4006/3/ADRIAN%20SOON%20BEE%20TIONG%20WATERMARK.pdf |
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| Summary: | Depth estimation of an object or a scene are used for the purpose of motion detection,
obstacle detection, positioning, depth mapping, or 3D shape recovery. These
capabilities can be applied in home, industry, medical, education and other areas of
applications. There are different types of depth sensor based on different technology,
which suit different kinds of applications. Depth sensors can be divided into active
sensor that emits out energy signal and passive sensor that does not require emission
of energy signal. Camera-based depth sensor such as stereo camera and monocular
camera are passive sensor. Hence, they do not have external or mutual interference
problem, no emission hazard, better object detectability, while having the advantage
of visual information. Compared to monocular camera, depth sensing with stereo
camera vision has longer depth range. However, stereo camera faces challenges from
occlusion, radiometric distortion, depth discontinuity, homogenous regions, false
boundary problem, and reflection issues. Depth estimation with monocular camera
uses images acquired at different focus settings. This can be achieved by varying the
lens’ position or the lens’ optical power. Past works on depth sensing with variable
focus mechanically actuates the lens position. The moving of the lens position results
in change of field of view or magnification in the images, a phenomenon known as
lens breathing. Image stacks acquired with linear actuator lens needs to be aligned
before being processed, which adds on the complexity of image alignment,
processing time, and dependence on the accuracy of image alignment. The developed
liquid lens monocular camera system for depth estimation showed successful depth
estimation with depth from focus technique without the need for image alignment.
Lens breathing is avoided by varying the thickness of the lens to change the focal
length without affecting the field of view. This research characterises the liquid lens
monocular camera for depth estimation of a moving object that utilizes liquid lens to
eliminate lens breathing. The response time of the liquid lens monocular camera
system to complete a successful image acquisition at each lens’ voltage change was
vi
0.274 s. A function describing the relationship between the liquid lens’ voltage,
liquid lens’ temperature and object distance is presented, based on experimental
setup for object at 1 m to 8 m distance. In the second research studies, an object�based focus measure method based on the mean of sum of modified Laplacian (SML)
of the edge and texture features of an object image area is presented. In the third
research work, an automated depth estimation using liquid lens camera system is
proposed. Based on the experiment for object distance range of 1 m to 8 m with
depth resolution of 1 m and 1.5 m, the root-mean-square error (RMSE) for depth
estimation of static object was 21%. Depth estimation of moving object shows
standard deviation of the steady-state error of 0.78 m and the RMSE was 1.2 m. The
estimated speed of the moving object was 0.47 m/s. Based on the results, the method
accurately estimated depth for static object distance of 1 m to 5 m and for moving
object was 1 m to 4 m. |
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