Visual odometry with unsynchronized multi-cameras setup for intelligent vehicle application

  title={Visual odometry with unsynchronized multi-cameras setup for intelligent vehicle application},
  author={R. Mhiri and P. Vasseur and S. Mousset and R{\'e}mi Boutteau and A. Bensrhair},
  journal={2014 IEEE Intelligent Vehicles Symposium Proceedings},
This paper presents a visual odometry with metric scale estimation of a multi-camera system in challenging un-synchronized setup. The intended application is in the field of intelligent vehicles. We propose a new algorithm named “triangle-based” method. The proposed algorithm employs the information from both extrinsic and intrinsic parameters of calibrated cameras. We assume that the trajectory between two consecutive frames of a camera is a linear segment (straight trajectory). The relative… Expand
Accurate scale estimation based on unsynchronized camera network
This paper presents an unsynchronized camera network able to estimate the motion and the structure with accurate absolute scale and shows quantitative evaluation through comparisons against GPS/INS ground truth. Expand
2D–3D synchronous/asynchronous camera fusion for visual odometry
A robust and direct 2D–3D registration method for camera synchronization and a visual odometry framework that benefits from both 2D and 3D acquisitions is proposed. Expand
Obstacle detection using unsynchronized multi-camera network
A simple algorithm for obstacle detection, road surface extraction and tracking using Kalman filter and u-v-disparity images and the use of sparse maps instead of dense ones due to the unsynchronization constraint is presented. Expand
Multi Camera System Analysis for Autonomous Navigation using End-to-End Deep Learning
The experimental results demonstrated that a multi-camera solution, based on 3 cameras, allow us to obtain better autonomous navigation control results in a End-to-End Deep Learning based approch, with a very small error when using the proposed camera configurations. Expand
Trajectory estimation and optimization through loop closure detection, using omnidirectional imaging and global-appearance descriptors
A framework to create a model of a priori unknown environments is presented, which is based on the global appearance of images, and includes a schema that fuses the information extracted from the scenes with the angle information provided by the odometry of the robot, considering the relative reliability of each piece of information. Expand
End-to-End Deep Learning Applied in Autonomous Navigation using Multi-Cameras System with RGB and Depth Images
A methodology was developed to allow working with RGB and depth images, which were obtained through a Microsoft Kinect V2 sensor device, and shows the importance of the use of multi-cameras systems for a better performance of autonomous navigation systems based on End-to-End learning approach. Expand
Brno Urban Dataset - The New Data for Self-Driving Agents and Mapping Tasks
A new dataset recorded in Brno - Czech Republic which offers data from four WUXGA cameras, two 3D LiDARs, inertial measurement unit, infrared camera and especially differential RTK GNSS receiver with centimetre accuracy which, to the best knowledge, is not available from any other public dataset so far. Expand
Three-dimensional reconstruction from heterogeneous video devices with camera-in-view information
  • S. Milani
  • Computer Science
  • 2015 IEEE International Conference on Image Processing (ICIP)
  • 2015
A 3D modelization of the surrounding environment is enabled with an improvised ad-hoc camera networks of both static and mobile devices and the estimation can be significantly improved whenever one or more cameras can be localized within the field of view of other devices. Expand
Approches 2D/2D pour le SFM à partir d'un réseau de caméras asynchrones. (2D/2D approaches for SFM using an asynchronous multi-camera network)
Une etape fondamentale pour ces systemes porte sur l'estimation du mouvement et de the structure de l'environnement (Structure From Motion) pour accomplir plusieurs tâches, notamment the detection d'obstacles and de marquage routier, the localisation and the cartographie. Expand
Estimation du mouvement et de la structure à l'échelle absolue à partir d'un réseau multi-caméras non synchronisées
Nous proposons un systeme de vision, base sur un reseau de cameras non-synchronisees permettant d'estimer le mouvement d'un vehicule et la structure de l'environnement 3D a l'echelle absolue.Expand


Real-time 6D stereo Visual Odometry with non-overlapping fields of view
The proposed technique is robust to outliers and able to continuously deliver a reasonable measurement of the scale factor, and is demonstrated by a concise evaluation on indoor datasets, including a comparison to accurate ground truth data provided by an external motion tracking system. Expand
Real-time monocular visual odometry for on-road vehicles with 1-point RANSAC
It is shown that by exploiting the nonholonomic constraints of wheeled vehicles it is possible to use a restrictive motion model which allows us to parameterize the motion with only 1 feature correspondence, which results in the most efficient algorithms for removing outliers. Expand
Motion Estimation for Self-Driving Cars with a Generalized Camera
A visual ego-motion estimation algorithm for a self-driving car equipped with a close-to-market multi-camera system that leads to a novel 2-point minimal solution for the generalized essential matrix where the full relative motion including metric scale can be obtained. Expand
Structure from stereo vision using unsynchronized cameras for simultaneous localization and mapping
In an indoor environment, the method typically results in 3D structure with approximately 200 feature points, with a median 3D accuracy of 1.6 cm when the average depth is 3 m and the robot has moved 1-2 cm between each image acquisition. Expand
Vision meets robotics: The KITTI dataset
A novel dataset captured from a VW station wagon for use in mobile robotics and autonomous driving research, using a variety of sensor modalities such as high-resolution color and grayscale stereo cameras and a high-precision GPS/IMU inertial navigation system. Expand
Five-Point Motion Estimation Made Easy
  • Hongdong Li, R. Hartley
  • Mathematics, Computer Science
  • 18th International Conference on Pattern Recognition (ICPR'06)
  • 2006
This paper provides a simpler algorithm based on the hidden variable resultant technique, which eliminates many unknowns at once in the equation solving stage and compute the minimal singular vector of the coefficient matrix, by which all the unknown parameters can be estimated simultaneously. Expand
A constricted bundle adjustment parameterization for relative scale estimation in visual odometry
This paper introduces a constricted parameterization of the bundle adjustment problem, where only the distances between neighboring cameras are optimized, while the rotation angles and translation directions stay fixed. Expand
Dense visual mapping of large scale environments for real-time localisation
A spherical ego-centric representation of the environment is proposed that is able to reproduce photo-realistic omnidirectional views of captured environments and is used for real-time model-based localisation and navigation. Expand
Are we ready for autonomous driving? The KITTI vision benchmark suite
The autonomous driving platform is used to develop novel challenging benchmarks for the tasks of stereo, optical flow, visual odometry/SLAM and 3D object detection, revealing that methods ranking high on established datasets such as Middlebury perform below average when being moved outside the laboratory to the real world. Expand
Monocular-SLAM-based navigation for autonomous micro helicopters in GPS-denied environments
The here-presented work describes the first aerial vehicle that uses onboard monocular vision as a main sensor to navigate through an unknown GPS-denied environment and independently of any external artificial aids. Expand