By using OpenCV, E gives 1 result, and H gives 2 results, satisfying the criteria that points are in front of camera. This is a matlab tutorial of monocular visual odometry. In this approach we have a camera (or an array of cameras) rigidly attached to a moving object (such as a car or a robot), and our job is to construct a 6-DOF trajectory using the video stream coming from this camera (s). Monocular visual odometry for autonomous navigation systems. A tag already exists with the provided branch name. I haven't figure out why. For inferring egomotion, their training approach treats . Powerful algorithms have been developed. Image features: Download this lib here: https://github.com/strasdat/Sophus. Because the images from KITTI have been undistorted, this step can be ignored. It's about matrix arithmetic. KIT 0 share Higher level functionality in autonomous driving depends strongly on a precise motion estimate of the vehicle. In this Computer Vision Video, we are going to take a look at Visual Odometry with a Monocular Camera. This will open up the calibration window. (2) Eigen 3 Then, in my CMakeLists.txt, I add this: set (THIRD_PARTY_LIBS libSophus.so ). 1.2 Application Visual Odometry was originally intended to be used on Mars Rover [5], where Visual odometry is the process of estimating the position and orientation of a camera by analyzing the images associated to it. 1 Paper Code EndoSLAM Dataset and An Unsupervised Monocular Visual Odometry and Depth Estimation Approach for Endoscopic Videos: Endo-SfMLearner CapsuleEndoscope/EndoSLAM 30 Jun 2020 Add a description, image, and links to the The review article extract data from KITTI dataset, and our group try to implement it in real time by using Kinect in robot. Monocular Visual Odometry Pose Estimation Pose Prediction Self-Supervised Learning Visual Odometry Datasets Edit KITTI TUM RGB-D Results from the Paper Edit Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers. (2) Matlab VO tutorial: This project is using monocular visual odometry to track the robot motion trajectory in a 2-D image. This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository. There was a problem preparing your codespace, please try again. Monocular Visual Odometry . to use Codespaces. Functions are declared in include/. Apply optimization to the previous N frames, where the cost function is the sum of reprojection error of each 3d-2d point pair. In the above figure: Graph/Connections between map points and frames: Github: https://github.com/AmanVirm. A tag already exists with the provided branch name. - GitHub - Samorange1/Monocular-Visual-Odometry: Using basic computer vision concepts like Optical flow, RANSAC and Essential Matrix, to recover pose from a car moving around the city. Skip to content Product Solutions Open Source Pricing Sign in Sign up Dataset: KITTI Before it, use RANSAC (Random sample consensus) to fit the corresponding feature points between two images. Detectors FAST SuperPoint Trackers Optical Flow Nearest Neighbor Image Source Local image files Camera Ground truth source Local ground truth file (KITTI dataset) Roadmap Analyse current VO system performance in dynamic scenes. Red markers on white line are the keyframes. In this paper, a hybrid sparse visual odometry (HSO) algorithm with online photometric calibration is proposed for monocular vision. It has been used in a wide variety of robotic applications, such as on the Mars Exploration Rovers. Python implementation of a basic monocular visual odometry algorithm. Environment OpenCV Numpy Usage A priori image is acquired through this camera. Two methods are implemented, where good match is: (2) Ratio of smallest and second smallest distance is smaller than threshold, proposed in Prof. Lowe's 2004 SIFT paper. A priori image is acquired through this camera. These points are called map points and are pushed to local map. If a inlier cv::KeyPoint hasn't been triangulated before, then triangulate it and push it to local map. Main scripts and classes for VO are in include/my_slam/vo/. Insert keyframe: If the relative pose between current frame and previous keyframe is large enough with a translation or rotation larger than the threshold, insert current frame as a keyframe. Using basic computer vision concepts like Optical flow, RANSAC and Essential Matrix, to recover pose from a car moving around the city. The implementation that I describe in this post is once again freely available on github . I guess its due to too few detected keypoints, which causes too few keypoints matches. Clean up local map: Remove map points that are: (1) not in current view, (2) whose view_angle is larger than threshold, (3) rarely be matched as inlier point. Topic: monocular-visual-odometry Goto Github. Simultaneous Visual Odometry, Object Detection, and Instance Segmentation, a list of papers, code, and other resources focus on deep learning SLAM system, Monocular CubeSLAM implementation without ROS integration, An attempt to implement a simple monocular camera based visual odometry from scratch, Dense Prediction Transformer for scale estimation in monocular visual odometry, Master Thesis about Monocular Visual Odometry. PDF Abstract Code Edit No code implementations yet. kandi ratings - Low support, No Bugs, No Vulnerabilities. This VO is achieved by the following procedures/algorithms: Estimate relative camera pose: It returns huge error. I released it for educational purposes, for a computer vision class I taught. Tutorial for install OpenCV 4.0: link. Learn more. Are you sure you want to create this branch? In this paper, we present VINS-Mono: a robust and versatile monocular visual-inertial state estimator. Feature matching: First of all, we will talk about what visual odometry . Work fast with our official CLI. config.txt Powerful algorithms have been developed. If there is an error of "unit_complex_.real() = 1.;" It's also my final project for the course EESC-432 Advanced Computer Vision in NWU in 2019 March. Because we use monocular visual, we can just get the relative positions of the points and it is not possible to obtain the absolute scale of the trajectory (Nister, 2004). Implement Monocular-visual-odometry with how-to, Q&A, fixes, code snippets. 1.1 Why Monocular? This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository. In this paper, we propose a novel approach for pose estimation with sensors held in hand based on monocular Visual Odometry and Pedestrian Dead-Reckoning. As for removing vectors with errors, you should filter keypoints in accordance with status returned by calcOpticalFlowPyrLK. You signed in with another tab or window. When modelling the geometric consistency within adjacent frames, most deep VO methods ignore the temporal continuity of the camera pose, which results in a very severe jagged uctuation in the velocity curves. to use Codespaces. (See Slambook Chapter 9.4.). kandi ratings - Low support, No Bugs, No Vulnerabilities. It is meant to compliment the capabilities of the traditional white cane. It has a more clear decription about the algorithms than this README, so I suggest to read it. The following code can help you with it: Secondly, undistort the images. topic page so that developers can more easily learn about it. This project tries to use monocular visual odometry to track the trajectory of robot and map the trajectory in a 2-D image. It the numbers of features in image is smaller than a threshold,a new detection will be triggered. Extract ORB keypoints and features. Based on the work of: https://github.com/uoip/monoVO-python, MANGAng solution for the KDD BR Competition 2022 - Visual odometry for autonomous UAVs. Are you sure you want to create this branch? sign in This example is based on opencv for face detection.The distance from the camera of the laptop to the face is measured. Utilize epipolar constraint to do feature matching. This is by no means a new concept. The copied functions are checkEssentialScore and checkHomographyScore in motion_estimation.h. Monocular Visual Odometry in JdeRobot infrastructure. You can download video here. By taking the raw monocular image sequence and IMU mea- surements as input, the visual-inertial odometry networks estimate the ego-motion (see Sec.3.2). These are done by g2o and its built-in datatypes of VertexSBAPointXYZ, VertexSE3Expmap, and EdgeProjectXYZ2UV. I borrowed its code of the criteria for choosing Essential or Homography (for decomposition to obtain relative camera pose.). python odometry.py Apply movement detection algorithm to improve VO. To associate your repository with the A human motion analysis from inertial data, i.e., a step length estimation, is used to dynamically solve the scale ambiguity and suppress the scale drift. In this paper, we propose to leverage deep monocular depth prediction to overcome limitations of geometry-based monocular visual odometry. Agrawal et al. Related Topics: Here are 17 public repositories matching this topic. The algorithm can be concluded into six steps. (WARNING: Hi, I'm sorry that this project is tuned for course demo, not for real world applications !!!). Do cmake, make, make install. Based on the work of: https://github.com/uoip/monoVO-python python3 ros monocular-visual-odometry Updated on Apr 11, 2020 Python amohap / vamr-project Star 0 Code Issues Pull requests Computer Vision Project for the Vision Algorithms for Mobile Robotics Class 2021 No ".so" or ".a" files.). ROS-based monocular vision algorithm. First install either of the following two packages: $ sudo apt-get install libsuitesparse Skip to content Product Solutions Open Source There was a problem preparing your codespace, please try again. I started developing it for fun as a python programming exercise, during my free time. Given a video, set the 1st frame(image) as reference, and do feature matching with the 2nd frame. Left is a video and the detected key points. Insert both 1st and K_th frame as keyframe. I referenced this structure from the Slambook Chapter 9. However, estimating a global scale from monocular images is inherently ambiguous (Eigen et al., 2014). Many monocular visual SLAM algorithms are derived from incremental structure-from-motion (SfM) methods. Their approach however is limited to stereo visual odometry. Despite all efforts, visual odometry is insufficient in real-time localization and vSLAM methods come on the scene as a solution which can be tested only via a comprehensive vSLAM dataset with accurate ground truths. If the median triangulation angle is smaller than threshold, I will abandon this 2nd frame, and repeat the above process on frame 3, 4, etc. First, find map points that are in the camera view. replace it and its following line with "unit_complex_ = std::complex(1,0);". Scaled Monocular Visual Odometry. This example shows you how to estimate the trajectory of a single. Monocular Visual Odometry odometry.cpp - calculates Dx,Dy,phi,Z {x-translation,y-translation,angle,depth} It also has various options to choose for feature detection, extraction, mathcing, finding good matches, and using different solving algorithms. The file paths have already been configured, so you don't need to change anything at this moment. The distance from the object to the monocular camera is roughly estimated by opencv. The first one is adopted, which is easier to tune the parameters to generate fewer error matches. Here are some examples (by no means a comprehensive list): NASA used visual odometry on Mars: Two Years of Visual Odometry on the Mars Exploration Rovers ( pdf) The monocular approach is still interesting because the stereo case degener-ates to the monocular case when the baseline is too small as compared to the distances of landmarks from the camera. I did this project after I read the Slambook. Are you sure you want to create this branch? Monocular-Visual-Odometry The goal of the project This project tries to use monocular visual odometry to track the trajectory of robot and map the trajectory in a 2-D image. See Slambook Chapter 4 and Chapter 7.8.2 for more details. For E, only single result to choose; For H, choose the one that makes the image plane and world-points plane more parallel. In robotics and computer vision, visual odometry is the process of determining the position and orientation of a robot by analyzing the associated camera images. The challenge is to devolop a standalone Visual based system for a Monocular Visual System. Unlike geometry based monocular methods, the proposed method can recover the absolute scale of the scene . Download here: https://github.com/RainerKuemmerle/g2o. Visual odometry is used in a variety of applications, such as mobile robots, self-driving cars, and unmanned aerial vehicles. [1] propose the use of ego-motion vector as a weak supervisory signal for feature learning. Change scale: Then, take a look at the configurations in config/config.yaml. You signed in with another tab or window. Monocular Visual Odometry For a while now I have been looking for ways to use (computer) vision to get odometry information. A demo: In the above figure: Left is a video and the detected key points. In Singhs article, the input dataset is from KITTI. (2) Optimize on map points and current camera pose. The framework of my program is based on Chapter 9 of Slambook, which is a RGB-D visual odometry project. However, their great majority focuses on either binocular imagery or pure LIDAR measurements. The review article extract data from KITTI dataset, and our group try to implement it in real time by using Kinect in robot. This work proposes a novel approach, which tracks the pose of monocular camera with respect to a given 3D LiDAR map, which employs a visual odometry system based on local bundle adjustment to reconstruct a sparse set of 3D points from image features. During triangulation, I also update the 2d-3d correspondance between current keypoints and triangulated mappoints, by either a direct link or going through previous keypoints that have been triangulated. Watch on If you observe the result closely you will notice that during the initial part of the path the predicted path more or less closely follows the actual path but during the latter part of the path the predicted path deviates largely from the actual path. If certain region of the image has only few keypoints, then extract more. The visual data from the monocular camera is fused with onboard IMU to develop indoor control and navigation algorithms. Finally, get scale information from some external source (like a speedometer. Do cmake and make. . Then, scale the map points correspondingly. Some thing interesting about monocular-visual-odometry. (1) Feature's distance is smaller than threshold, described in Slambook. $ sudo apt-get install libsuitesparse-dev. If nothing happens, download Xcode and try again. Visual Odometry trajectory visualization from Monocular Images, Tutorial code for "AirLab Summer School Session 2.1". Many Git commands accept both tag and branch names, so creating this branch may cause unexpected behavior. Tools Used Macbook Pro 2015, 13'' Open CV Python 3.6 MATLAB Many Git commands accept both tag and branch names, so creating this branch may cause unexpected behavior. Novel filtering techniques are used to cope with inconsistencies with the estimation of the essential matrix. The solution I guess is to use the ORB-SLAM's method for extracting enough uniformly destributed keypoints across different scales, and doing guided matching based on the estimated camera motion. sual odometry), a self-supervised learning based monocular visual odometry (VO) for road vehicles. The dataset has been undistorted. Install by: (Note: Eigen only has header files. Points are the map points, where points with red color are newly triangulated. See videos below: The result shows: (1) Optimization improves accuracy. A toy implementation of a Visual Odometry (VO) pipeline in Python Aug 30, 2019 5 min read pySLAM pySLAM is a 'toy' implementation of a monocular Visual Odometry (VO) pipeline in Python. A monocular visual odometry (VO) with 4 components: initialization, tracking, local map, and bundle adjustment. LIMO: Lidar-Monocular Visual Odometry Abstract: Higher level functionality in autonomous driving depends strongly on a precise motion estimate of the vehicle. However, their great majority focuses on either binocular imagery or pure LIDAR measurements. To devolop a system that tracks movoment of a system in real time based on a visual Odometry. Scale the translation t to be the same length as the ground truth, so that I can make comparison with ground truth. Loop closure detection with DBoW2 using mez's monocular VO. The optical flow vector of a moving object in a video sequence. 1.2 Application Visual Odometry was originally intended to be used on Mars Rover [5], where If nothing happens, download Xcode and try again. Detailed quantitative and qualitative evaluations of the proposed framework on the KITTI and Cityscapes datasets show that the proposed method outperforms both existing traditional and unsupervised deep VO methods providing better results for both pose estimation and depth recovery. abedinsherifi / landmark-detection-localization Python 1.0 1.0 0.0. Visual Odometry is an important area of information fusion in which the central aim is to estimate the pose of a robot using data collected by visual sensors. Monocular Visual Odometry using OpenCV Jun 8, 2015 8 minute read Last month, I made a post on Stereo Visual Odometry and its implementation in MATLAB. Some of its folders contain a README. GitHub - ossamaAhmed/monocular_visual_odometry: Implemented a monocular visual odometry (VO) pipeline with the most essential features: initialization of 3D landmarks, keypoint tracking between two frames, pose estimation using established 2D 3D correspondences, and triangulation of new land- marks. You signed in with another tab or window. any workflow Packages Host and manage packages Security Find and fix vulnerabilities Codespaces Instant dev environments Copilot Write better code with Code review Manage code changes Issues Plan and track work Discussions Collaborate outside code Explore All. This post would be focussing on Monocular Visual Odometry, and how we can implement it in OpenCV/C++ . No License, Build not available. sign in (1) Slambook: The book provides both vSLAM theory as well as easy-to-read code examples in every chapter. Decompose E or H into the relative pose between two frames, which is the rotation (R) and translation (t). Monocular-Visual-Odometry The distance from the object to the monocular camera is roughly estimated by opencv. It helped me a lot for getting clear the whole workflow. Output: This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository. Estimate camera pose by RANSAC and PnP. However, when we do track in real time, this step is necessary. Monocular VO uses the information from images produced by a single I tested my VO with 3 different settings: (1) No optimization. The monocular approach is still interesting because the stereo case degener-ates to the monocular case when the baseline is too small as compared to the distances of landmarks from the camera. image_path : Path to a priori image These files are mainly copied or built on top of the Slambook's code: I also borrowed other codes from the slambook. I read this Dr. Xiang Gao's Slambook before writing code. 3. In bundle adjustment, I cannot optimize (1) multiple frames and (b) map points at the same time. LIMO: Lidar-Monocular Visual Odometry 07/19/2018 by Johannes Graeter, et al. When we are using just one camera, it's called Monocular Visual Odometry. You signed in with another tab or window. The way you use that is as follows: python calculate_focal_length.py [pxW] [f_mm] [fov] where: pxW is the width of the images in pixels. Computer Vision Project for the Vision Algorithms for Mobile Robotics Class 2021. Second, we adopt a recent global SfM method for the pose-graph optimization, which . Please HSO introduces two novel measures, that is, direct image alignment with adaptive mode selection and image photometric description using ratio factors, to enhance the robustness against dramatic image intensity . Learn more. In this work we present WGANVO, a Deep Learning based monocular Visual Odometry method. Are you sure you want to create this branch? The training is performed using a semi-supervised approach. Scale drift is a crucial challenge for monocular autonomous driving to emulate the performance of stereo. It's based on Eigen, and contains datatypes for Lie Group and Lie Algebra (SE3/SO3/se3/so3). KNOWN_DISTANCE : The actual distance from the object of the prior image to the camera You signed in with another tab or window. Using basic computer vision concepts like Optical flow, RANSAC and Essential Matrix, to recover pose from a car moving around the city. My pdf-version course report is here. Keyframe and local map: Visual odometry is used in a variety of applications, such as mobile robots, self-driving cars, and unmanned aerial vehicles. In particular, a neural network is trained to regress a pose estimate from an image pair. The dataset has been undistorted. This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository. It's also my final project for the course EESC-432 Advanced Computer Vision in NWU in 2019 March. A simple monocular visual odometry (part of vSLAM) by ORB keypoints with initialization, tracking, local map and bundle adjustment. Visual odometry is the process of determining the location and orientation of a camera by analyzing a sequence of images. Classifier_path : Path to a detector. After PnP, based on the 3d-2d correspondances, I update the connectionts between map points and current keypoints. Do feature matching to find 2d-3d correspondance between 3d map points and 2d image keypoints. Then, a simple grid sampling is applied to obtain keypoints uniformly distributed across image. The. Source: Bi-objective Optimization for Robust RGB-D Visual Odometry Benchmarks Add a Result These leaderboards are used to track progress in Visual Odometry (2) The estiamted trajectory is close to the ground truth. This project can be used in the situation which GPS and wheel odometry become unreliable and it also can be used to calibrate the position with other methods. Python, OpenCV library were used, video datasets were used to benchmark the system. Summary. With the observation that road . Work fast with our official CLI. Right is the camera trajectory corresponding to the left video: White line is from VO; Green line is ground truth. Fourthly, calculate the essential matrix by using five-point algorithm (Nister, 2004). GitHub - karanchawla/Monocular-Visual-Inertial-Odometry: This contains the code (in development) for monocular visual odometry of a quadrotor. See its official page. As an effective complement to other sensors such as GPS, Inertial Navigation System (INS) and wheel odometry, etc., monocular VO is popular for its low cost and easy access. Since I failed to make install it, I manually moved /Sophus/sophus to /usr/include/sophus, and moved libSophus.so to usr/lib. If at frame K, the triangulation angle is large than threshold, the initialization is completed. Monocular Visual Odometry Visual odometry is the process of determining the location and orientation of a camera by analyzing a sequence of images. By computing the deriviate wrt (1) points 3d pos and (2) camera poses, we can solve the optimization problem using Gauss-Newton Method and its variants. Unsupervised Learning based monocular visual odometry (VO) has lately drawn significant attention for its potential in label-free leaning ability and robustness to camera parameters and environmental variations. Thirdly, use FAST algorithm to detect features in image , then use KLT tracker to track these features in the next image . Monocular Visual Odometry (VO) is an alternative nav-igation solution that has made signi cant progress in the last decade, only recently producing viable solutions that can be run on small mobile platforms with limited resources. The results are shown below. monocular-visual-odometry 112 PDF View 1 excerpt Visual-lidar odometry and mapping: low-drift, robust, and fast I did this project after I read the Slambook. Methods Edit 1x1 Convolution Landmark detection and localization project using python. 3.1 Depth Estimation I tested the current implementation on TUM fr1_desk and fr1_xyz dataset, but both performances are bad. Monocular visual odometry has attracted more and more attention for its wide applications in robotics, autonomous driving and augmented reality (AR). This paper presents a real-time monocular SFM system that corrects for scale drift using a novel cue combination framework for ground plane estimation, yielding accuracy comparable to stereo over long driving sequences. Do feature matching between current and previous keyframe. See the tree structure for overview: Require: OpenCV, Eigen, Sophus, g2o. In short, the Slambook provides huge help for me and my this project. Graphs are built at two stages of the algorithm: Since I've built the graph in previous step, I know what the 3d-2d point correspondances are in all frames. Compute their Symmetric Transfer Error by method in ORB-SLAM paper and choose the better one (i.e., choose H if H/(E+H)>0.45). Use Git or checkout with SVN using the web URL. But since they are small pieces and lines, I didn't list them here. A visual-odometry based ROS mapping package. Despite bad performance on fr1 dataset, my program does work well on this New Tsukuba Stereo Database, whose images and scenes are synthetic and have abundant high quality keypoints. Our approach starts with a robust procedure for estimator . Monocular visual odometry approaches that purely rely on geometric cues are prone to scale drift and require sufficient motion parallax in successive frames for motion estimation and 3D reconstruction. Check Triangulation Result To calculate the focal length of your image, I have written a simple helper Python script. Visual odometry is the process of determining the location and orientation of a camera by analyzing a sequence of images. UZH Robotics and Perception Group 10.9K subscribers We propose a semi-direct monocular visual odometry algorithm that is precise, robust, and faster than current state-of-the-art methods. This paper proposes a novel approach for extending monocular visual odometry to a stereo camera system. No License, Build available. Since Slambook doesn't write a lot about monocular VO, I resorted to this Matlab tutorial for solution. Checkout to the last version in year 2017. Fifthly, use SVD (singular value decomposition) to estimate R, t from the essential matrix. The dataset I used is also the same as this Matlab tutorial, which is the New Tsukuba Stereo Database. f_mm is the focal length of the camera that was used to capture the image in [mm]. However, partially due to the lack of drift correction technique, these methods are still by far less accurate than geometric approaches for large-scale odometry estimation. Please This project is using monocular visual odometry to track the robot motion trajectory in a 2-D image. Using basic computer vision concepts like Optical flow, RANSAC and Essential Matrix, to recover pose from a car moving around the city. It can provide earlier warnings, which allow the user to navigate more safely in potentially challenging situations. Implement Monocular-Visual-Odometry with how-to, Q&A, fixes, code snippets. monocular-visual-odometry simplescreenrecorder-2018-10-22_17.46.12.mkv. A tag already exists with the provided branch name. See details below: (1) OpenCV 4.0 topic, visit your repo's landing page and select "manage topics.". If nothing happens, download GitHub Desktop and try again. Get inliers by epipoloar constraint. First, we solve the visual odometry problem by a novel rank-1 matrix factorization technique which is more robust to the errors in map initialization. Use Git or checkout with SVN using the web URL. Classes declared in include/vo/ are based on this Chapter. KNOWN_WIDTH : The actual width of the object in the prior image A tag already exists with the provided branch name. One camera and one low-cost inertial measurement unit (IMU) form a monocular visual-inertial system (VINS), which is the minimum sensor suite (in size, weight, and power) for the metric six degrees-of-freedom (DOF) state estimation. The only visual odometry approach using deep learning that the authors are aware of the work of Konda and Memisevic [19]. Paper Add Code Lateral Ego-Vehicle Control without Supervision using Point Clouds no code yet 20 Mar 2022 In this paper, a framework for training a more robust and scalable model for lateral vehicle control is proposed. Visual odometry. To run it for a monocular camera using an 8x6 chessboard with 24mm squares just type: rosrun camera_calibration cameracalibrator.py --size 8x6 --square 0.024 image:=/raspicam/image_raw You will see a new window opened which will highlight the checkerboard:. (3) Optimize on previous 5 camera poses. Many Git commands accept both tag and branch names, so creating this branch may cause unexpected behavior. The whole frame- work is trained in a sliding window optimization strategy that includes two parts: intra-window optimization and inter- window optimization (see Sec.3.3). EGS is a guidance system aimed at visually impaired individuals. Keep on estimating the next camera pose. filterHomographyDecompByVisibleRefpoints, which appears in OpenCV 3.4.5. If nothing happens, download GitHub Desktop and try again. Many Git commands accept both tag and branch names, so creating this branch may cause unexpected behavior. In Singhs article, the input dataset is from KITTI. A visual-odometry based ROS mapping package. 1.1 Why Monocular? A monocular visual odometry (VO) with 4 components: initialization, tracking, local map, and bundle adjustment. You may need a version newer than 3.4.5, because I used this function: Compute the Essential Matrix (E) and Homography Matrix (H) between the two frames. The review articles are Monocular Visual Odometry using OpenCV (Singh, 2015) and An Efficient Solution to the Five-Point Relative Pose Problem (Nister, 2004). 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