Motion In 3D Space Research Articles

Sensor fusion of cameras and a laser for city-scale 3D reconstruction.

This paper presents a sensor fusion system of cameras and a 2D laser sensor for large-scale 3D reconstruction. The proposed system is designed to capture data on a fast-moving ground vehicle. The system consists of six cameras and one 2D laser sensor, and they are synchronized by a hardware trigger. Reconstruction of 3D structures is done by estimating frame-by-frame motion and accumulating vertical laser scans, as in previous works. However, our approach does not assume near 2D motion, but estimates free motion (including absolute scale) in 3D space using both laser data and image features. In order to avoid the degeneration associated with typical three-point algorithms, we present a new algorithm that selects 3D points from two frames captured by multiple cameras. The problem of error accumulation is solved by loop closing, not by GPS. The experimental results show that the estimated path is successfully overlaid on the satellite images, such that the reconstruction result is very accurate.

Needle path planning and steering in a three-dimensional non-static environment using two-dimensional ultrasound images

Needle insertion is commonly performed in minimally invasive medical procedures such as biopsy and radiation cancer treatment. During such procedures, accurate needle tip placement is critical for correct diagnosis or successful treatment. Accurate placement of the needle tip inside tissue is challenging, especially when the target moves and anatomical obstacles must be avoided. We develop a needle steering system capable of autonomously and accurately guiding a steerable needle using two-dimensional (2D) ultrasound images. The needle is steered to a moving target while avoiding moving obstacles in a three-dimensional (3D) non-static environment. Using a 2D ultrasound imaging device, our system accurately tracks the needle tip motion in 3D space in order to estimate the tip pose. The needle tip pose is used by a rapidly exploring random tree-based motion planner to compute a feasible needle path to the target. The motion planner is sufficiently fast such that replanning can be performed repeatedly in a closed-loop manner. This enables the system to correct for perturbations in needle motion, and movement in obstacle and target locations. Our needle steering experiments in a soft-tissue phantom achieves maximum targeting errors of 0.86 ± 0.35 mm (without obstacles) and 2.16 ± 0.88 mm (with a moving obstacle).

Straight or curved? From deterministic to probabilistic models of 3D motion perception

Straight or curved? From deterministic to probabilistic models of 3D motion perception

3D Rotary Model Design Based on Accelerometer

Accelerometer is the important sensor of MEMS inertial sensors and is applied in many occasions. A three dimension model is designed to accomplish rotary motion in 3D space and the model is introduced to the computer input system to enhance the functions of the computer input system. In order to indicate the feasibility and effectiveness, a Demo platform with AVR controller is designed to control the rotary motion of accelerometer solid model.

Experimental testing and modeling of a tethered spherical aerostat in an outdoor environment

This paper focuses on an investigation of the dynamic characteristics of a spherical aerostat on a single tether. A test facility was constructed to gather experimental data required to characterize the system. Our experiments were all in the supercritical range at Reynolds numbers greater than 3.7×10 5. The balloon's drag coefficient was extracted from position measurements. We find that the balloon's large oscillations and surface roughness, combined with the wind turbulence, result in a substantial increase in the drag coefficient. To further study the system, a numerical simulation was developed. The aerostat was modeled as a single rigid body attached to a tether, and subject to buoyancy, aerodynamic drag and gravity. The tether was modeled using a lumped-mass approach, which includes internal stiffness and damping. The dynamic simulation of the aerostat was obtained by setting up the equations of motion in 3D space and integrating them numerically. Finally, the model was validated through comparison with experimental data and a modal analysis was performed.

Flying Object Control-Inertial Measurement Unit for An Embedded System

The project in global is intended to complex control of a mobile flying object with free motion in 3D space. The control is to be designed to work in the object's embedded system. The paper itself is partially focused on the first part of the project, 6DOF inertial measurement unit and on some algorithms to estimate orientation in space.

Compression of Human Motion Animation Using the Reduction of Interjoint Correlation

We propose two compression methods for the human motion in 3D space, based on the forward and inverse kinematics. In a motion chain, a movement of each joint is represented by a series of vector signals in 3D space. In general, specific types of joints such as end effectors often require higher precision than other general types of joints in, for example, CG animation and robot manipulation. The first method, which combines wavelet transform and forward kinematics, enables users to reconstruct the end effectors more precisely. Moreover, progressive decoding can be realized. The distortion of parent joint coming from quantization affects its child joint in turn and is accumulated to the end effector. To address this problem and to control the movement of the whole body, we propose a prediction method further based on the inverse kinematics. This method achieves efficient compression with a higher compression ratio and higher quality of the motion data. By comparing with some conventional methods, we demonstrate the advantage of ours with typical motions.

A 3-D marker-free system for the analysis of movement disabilities--an application to the legs.

The aim of this paper is to describe an approach allowing the analysis of human motion in three-dimensional (3-D) space. The system that we developed is composed of three charge-coupled-device cameras that capture synchronized image sequences of a human body in motion without the use of markers. Characteristic points belonging to the boundaries of the body in motion are first extracted from the initial images. Two-dimensional superquadrics are then adjusted on these points by a fuzzy clustering process. After that, the position of a 3-D model based on a set of articulated superquadrics, each of them describing a part of the human body, is reconstructed. An optical flow process allows the prediction of the position of the model from its position at the previous time, and gives initial values for the fuzzy classification. The results that we present concern more specifically the analysis of movement disabilities of a human leg during gait. They are improved by using articulation-based constraints. The methodology can be used in human motion analysis for clinical applications.