Stereo Vision-Based 3D Positioning and Tracking
The evolution of technologies for the capture of human movement has been motivated by a number of potential applications across a wide variety of fields. However, capturing human motion in 3D is difficult in an outdoor environment when it is performed without controlled surroundings. In this paper,...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2020-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9146158/ |
| _version_ | 1818917540638752768 |
|---|---|
| author | Atiqul Islam Md. Asikuzzaman Mohammad Omar Khyam Md. Noor-A-Rahim Mark R. Pickering |
| author_facet | Atiqul Islam Md. Asikuzzaman Mohammad Omar Khyam Md. Noor-A-Rahim Mark R. Pickering |
| author_sort | Atiqul Islam |
| collection | DOAJ |
| description | The evolution of technologies for the capture of human movement has been motivated by a number of potential applications across a wide variety of fields. However, capturing human motion in 3D is difficult in an outdoor environment when it is performed without controlled surroundings. In this paper, a stereo camera rig with an ultra-wide baseline distance and conventional cameras with fish-eye lenses is proposed. Its cameras provide a wide field of view (FOV) which increases the coverage area and also enables the baseline distance to be increased to cover the common area required for both cameras' views to perform as a stereo camera. We propose a passive marker-based approach to track the motion of the object. In this method, an adaptive thresholding method is applied to extract each small pink polyester marker from the video frames. As the cameras have fish-eye lenses, it is difficult to estimate the depth information using a pinhole camera model. We use a unique method to restore the 3D positions by developing a relationship between the pixel dimensions and distances in an image and real world coordinates. In this paper, occlusion detection is considered because, in the marker-based capturing of articulated human kinematics, the occlusion of a marker is one of the major challenges. The detection algorithm differentiates among types of occlusions and predicts any missing marker position where necessary. As this design is intended to be mounted on a moving carrier, such as a drone or car, a method for compensating the camera's ego-motion is proposed. The proposed 3D positioning and tracking system is tested in different situations to validate its applicability as a stereo camera rig as well as its performance for motion capture. The performance of the proposed system is compared with that of a standard motion capture system called Vicon and is shown to have the same order of accuracy while incurring less cost. |
| first_indexed | 2024-12-20T00:35:42Z |
| format | Article |
| id | doaj.art-2df512ada45b4a25b32cf4a85fe161df |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-20T00:35:42Z |
| publishDate | 2020-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-2df512ada45b4a25b32cf4a85fe161df2022-12-21T19:59:45ZengIEEEIEEE Access2169-35362020-01-01813877113878710.1109/ACCESS.2020.30113609146158Stereo Vision-Based 3D Positioning and TrackingAtiqul Islam0https://orcid.org/0000-0002-1432-1150Md. Asikuzzaman1https://orcid.org/0000-0003-2079-009XMohammad Omar Khyam2Md. Noor-A-Rahim3https://orcid.org/0000-0003-0587-3145Mark R. Pickering4https://orcid.org/0000-0001-6736-3859ANU College of Engineering and Computer Science, The Australian National University, Canberra, ACT, AustraliaSchool of Engineering and Information Technology, University of New South Wales, Canberra, ACT, AustraliaSchool of Engineering and Technology, Central Queensland University, Melbourne, VIC, AustraliaSchool of Computer Science and Information Technology, University College Cork, Cork 021, IrelandSchool of Engineering and Information Technology, University of New South Wales, Canberra, ACT, AustraliaThe evolution of technologies for the capture of human movement has been motivated by a number of potential applications across a wide variety of fields. However, capturing human motion in 3D is difficult in an outdoor environment when it is performed without controlled surroundings. In this paper, a stereo camera rig with an ultra-wide baseline distance and conventional cameras with fish-eye lenses is proposed. Its cameras provide a wide field of view (FOV) which increases the coverage area and also enables the baseline distance to be increased to cover the common area required for both cameras' views to perform as a stereo camera. We propose a passive marker-based approach to track the motion of the object. In this method, an adaptive thresholding method is applied to extract each small pink polyester marker from the video frames. As the cameras have fish-eye lenses, it is difficult to estimate the depth information using a pinhole camera model. We use a unique method to restore the 3D positions by developing a relationship between the pixel dimensions and distances in an image and real world coordinates. In this paper, occlusion detection is considered because, in the marker-based capturing of articulated human kinematics, the occlusion of a marker is one of the major challenges. The detection algorithm differentiates among types of occlusions and predicts any missing marker position where necessary. As this design is intended to be mounted on a moving carrier, such as a drone or car, a method for compensating the camera's ego-motion is proposed. The proposed 3D positioning and tracking system is tested in different situations to validate its applicability as a stereo camera rig as well as its performance for motion capture. The performance of the proposed system is compared with that of a standard motion capture system called Vicon and is shown to have the same order of accuracy while incurring less cost.https://ieeexplore.ieee.org/document/9146158/Motion capture3D positioningstereo visionmotion trackinghigh precision |
| spellingShingle | Atiqul Islam Md. Asikuzzaman Mohammad Omar Khyam Md. Noor-A-Rahim Mark R. Pickering Stereo Vision-Based 3D Positioning and Tracking IEEE Access Motion capture 3D positioning stereo vision motion tracking high precision |
| title | Stereo Vision-Based 3D Positioning and Tracking |
| title_full | Stereo Vision-Based 3D Positioning and Tracking |
| title_fullStr | Stereo Vision-Based 3D Positioning and Tracking |
| title_full_unstemmed | Stereo Vision-Based 3D Positioning and Tracking |
| title_short | Stereo Vision-Based 3D Positioning and Tracking |
| title_sort | stereo vision based 3d positioning and tracking |
| topic | Motion capture 3D positioning stereo vision motion tracking high precision |
| url | https://ieeexplore.ieee.org/document/9146158/ |
| work_keys_str_mv | AT atiqulislam stereovisionbased3dpositioningandtracking AT mdasikuzzaman stereovisionbased3dpositioningandtracking AT mohammadomarkhyam stereovisionbased3dpositioningandtracking AT mdnoorarahim stereovisionbased3dpositioningandtracking AT markrpickering stereovisionbased3dpositioningandtracking |