Affine Correspondences between Multi-Camera Systems for Relative Pose Estimation

We present a novel method to compute the relative pose of multi-camera systems using two affine correspondences (ACs). Existing solutions to the multi-camera relative pose estimation are either restricted to special cases of motion, have too high computational complexity, or require too many point correspondences (PCs). Thus, these solvers impede an efficient or accurate relative pose estimation when applying RANSAC as a robust estimator. This paper shows that the 6DOF relative pose estimation problem using ACs permits a feasible minimal solution, when exploiting the geometric constraints between ACs and multi-camera systems using a special parameterization. We present a problem formulation based on two ACs that encompass two common types of ACs across two views, i.e., inter-camera and intra-camera. Moreover, the framework for generating the minimal solvers can be extended to solve various relative pose estimation problems, e.g., 5DOF relative pose estimation with known rotation angle prior. Experiments on both virtual and real multi-camera systems prove that the proposed solvers are more efficient than the state-of-the-art algorithms, while resulting in a better relative pose accuracy. Source code is available at https://github.com/jizhaox/relpose-mcs-depth

Minimal Solvers for Relative Pose Estimation of Multi-Camera Systems using Affine Correspondences

We propose three novel solvers for estimating the relative pose of a multi-camera system from affine correspondences (ACs). A new constraint is derived interpreting the relationship of ACs and the generalized camera model. Using the constraint, we demonstrate efficient solvers for two types of motions. Considering that the cameras undergo planar motion, we propose a minimal solution using a single AC and a solver with two ACs to overcome the degenerate case. Also, we propose a minimal solution using two ACs (a minimal number of one AC and one point correspondence) with known vertical direction, e.g., from an IMU. Since the proposed methods require significantly fewer correspondences than state-of-the-art algorithms, they can be efficiently used within RANSAC for outlier removal and initial motion estimation. The solvers are tested both on synthetic data and on three real-world scenes. It is shown that the accuracy of the estimated poses is superior to the state-of-the-art techniques. Source code is released at https://github.com/jizhaox/relative_pose_gcam_affin

Minimal Solutions for Relative Pose with a Single Affine Correspondence

In this paper we present four cases of minimal solutions for two-view relative pose estimation by exploiting the affine transformation between feature points and we demonstrate efficient solvers for these cases. It is shown, that under the planar motion assumption or with knowledge of a vertical direction, a single affine correspondence is sufficient to recover the relative camera pose. The four cases considered are two-view planar relative motion for calibrated cameras as a closed-form and a least-squares solution, a closedform solution for unknown focal length and the case of a known vertical direction. These algorithms can be used efficiently for outlier detection within a RANSAC loop and for initial motion estimation. All the methods are evaluated on both synthetic data and real-world datasets from the KITTI benchmark. The experimental results demonstrate that our methods outperform comparable state-of-the-art methods in accuracy with the benefit of a reduced number of needed RANSAC iterations

Minimal Solutions for Relative Pose with a Single Affine Correspondence

In this paper we present four cases of minimal solutions for two-view relative pose estimation by exploiting the affine transformation between feature points and we demonstrate efficient solvers for these cases. It is shown, that under the planar motion assumption or with knowledge of a vertical direction, a single affine correspondence is sufficient to recover the relative camera pose. The four cases considered are two-view planar relative motion for calibrated cameras as a closed-form and a least-squares solution, a closed-form solution for unknown focal length and the case of a known vertical direction. These algorithms can be used efficiently for outlier detection within a RANSAC loop and for initial motion estimation. All the methods are evaluated on both synthetic data and real-world datasets from the KITTI benchmark. The experimental results demonstrate that our methods outperform comparable state-of-the-art methods in accuracy with the benefit of a reduced number of needed RANSAC iterations.Comment: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 202

Property and Structure Characterization of High Molecular Weight Polyacrylonitrile Polymers Initiated by 2,2'-Azobis (2-methyl propionamide) Dihydrochloride Using Aqueous Deposited Polymerization Technique

Powdery high molecular weight polyacrylonitrile (HMW-PAN) polymers were successfully synthesized by aqueous deposited polymerization (ADP) method with 2,2'-azobis (2-methyl propionamide) dihydrochloride (AIBA) as the initiator and itaconic acid (IA) as comonomer. The utilization of IA into the ADP system was conducive to relax the proceeding of thermo-oxidation process. Differential scanning calorimeter (DSC) curves of obtained PAN copolymers showed the doublet peaks character under air atmosphere, attributing to the exothermic cyclization and oxidative reactions during heat-treatment process. With the utilization of IA in the reaction system, crystallinity and grain sizes of the PAN polymers decreased. The stretching vibration of nitrile group (C≡N) at 2240cm-1 was the strongest peak in both Fourier transform infrared spectra (FTIR). And the stretching vibration and bending of CH2 were the stronger peaks in FTIR. Amido group (NH2), carbonyl group (C=O) and C-O single bond existed in FTIR of PAN homopolymer and copolymers, indicating occurrence of C≡N hydrolysis during polymerization process except carboxyl group (COOH) introduced by IA

Minimal Cases for Computing the Generalized Relative Pose Using Affine Correspondences

We propose three novel solvers for estimating the relative pose of a multi-camera system from affine correspondences (ACs). A new constraint is derived interpreting the relationship of ACs and the generalized camera model. Using the constraint, we demonstrate efficient solvers for two types of motions assumed. Considering that the cameras undergo planar motion, we propose a minimal solution using a single AC and a solver with two ACs to overcome the degenerate case. Also, we propose a minimal solution using two ACs with known vertical direction, e.g., from an IMU. Since the proposed methods require significantly fewer correspondences than state-of-the-art algorithms, they can be efficiently used within RANSAC for outlier removal and initial motion estimation. The solvers are tested both on synthetic data and on real-world scenes from the KITTI odometry benchmark. It is shown that the accuracy of the estimated poses is superior to the state-of-the-art techniques

Li2ZrO3-Coated Monocrystalline LiAl0.06Mn1.94O4 Particles as Cathode Materials for Lithium-Ion Batteries

Li2ZrO3-coated and Al-doped micro-sized monocrystalline LiMn2O4 powder is synthesized through solid-state reaction, and the electrochemical performance is investigated as cathode materials for lithium-ion batteries. It is found that Li2ZrO3-coated LiAl0.06Mn1.94O4 delivers a discharge capacity of 110.90 mAhg−1 with 94% capacity retention after 200 cycles at room temperature and a discharge capacity of 104.4 mAhg−1 with a capacity retention of 87.8% after 100 cycles at 55 °C. Moreover, Li2ZrO3-coated LiAl0.06Mn1.94O4 could retain 87.5% of its initial capacity at 5C rate. This superior cycling and rate performance can be greatly contributed to the synergistic effect of Al-doping and Li2ZrO3-coating