Stereo Vision-Based 3D Positioning and Tracking

Atiqul Islam,Mohammad Omar Khyam,Md Noor-A-Rahim,Md Asikuzzaman,Mark R Pickering

doi:10.1109/access.2020.3011360

Abstract

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.

Highlights

MoCap, a popular nickname for motion capture, often conjures up images of a human motion capture system (MCS) that records the movements of a human and uses the recorded data to analyze or animate them
EXPERIMENTAL RESULTS AND ANALYSIS the experimental data captured with the designed stereo camera rig and processed with the proposed algorithms were analyzed
Literature shows that many stateof-the-art 3D positioning and tracking methods have used known trajectories for evaluation purposes where tracking error was measured with respect to the known trajectories [43], [44]

Summary

INTRODUCTION

MoCap, a popular nickname for motion capture, often conjures up images of a human motion capture system (MCS) that records the movements of a human and uses the recorded data to analyze or animate them. Commercially available optical MCSs, such as Vicon [2], are very efficient at tracking the realistic motion of a subject, an expensive system setup with a large number of cameras inside a laboratory is required They are sensitive to lighting conditions, shadows and other factors that can interfere with light propagation. A. Islam et al.: Stereo Vision-Based 3D Positioning and Tracking attracted the attention of many researchers, with their wide range of applications requiring different levels of accuracy. Reconstructing a scene in 3D is performed via epipolar rectification, feature detection, and the matching and triangulation of the correspondences of the scene from two camera viewpoints This current study proposes to achieve motion capture using the described stereo vision technique.

RELATED WORK

PREPOSSESSING OF MARKERS

OCCLUSION DETECTION

CAMERA MOTION COMPENSATION

EXPERIMENTAL ANALYSIS

VIII. CONCLUSION