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The usage of a global positioning system (GPS) corrected inertial navigation system (INS) seems to be advantageous to camera-based pose estimation algorithms for outdoor navigation. The GPS signals lead to a geographical location with an accuracy of a few meters or even up to some centimeters in a setup utilizing correction data. Performing the pose estimation with a camera system has several disadvantages...
Due the recently increased number of survey papers, we consider important to offer an evaluation of the different types of current survey papers to assess their benefits and inform the readers regarding their categories. The field selected here is the Human Activity Recognition (HAR), although its idea can be applied to other research areas as well. Thus, a variety of survey papers are studied thoroughly...
In order to make the industrial robot catch the target object accurately, an automatic positioning system based on monocular vision is proposed in this paper. Specifically, efficient localization algorithms are applied to get the position information of the target object. Besides, in consideration of further application requirements, an additional recognition algorithm based on 2-1 Hough transform...
In this paper, we propose a hybrid metric for measuring the accuracy of the estimated camera. Existing camera pose evaluation methods are mainly built upon one of the two metrics: the geometric measurement or the photometric measurement. The geometric based method inspects the relative position between source and target points, while the photometric based method utilizes the pixel intensity as assessment...
We consider the task of determining the pose of a depth camera based on a single target depth image and a 3D model of the indoor environment that the image was taken in. We identify the quality of a pose estimate with summed differences between depth values in the target depth image and a depth image generated synthetically by using that pose estimate in the 3D model. We then propose an evolutionary...
Wide Area Motion Imagery (WAMI) are usually taken from unmaned air vehicles at low frame rates, and having very wide ground coverage. These images serve as rich source for many applications like surveillance, urban planing and traffic monitoring. Thus, understanding WAMI imagery exploitation has been gaining more interest recent years. In this paper, we focus on estimating the pose of vehicles in...
Real-time pose estimation is a challenge in multi-camera vision system due to the demand of rapid response, high accuracy and robustness. Although some works based on multi-camera have been proposed, few works have regarded multi-camera as a fixed integration, which is easier to apply in real robotic application than eye-in-hand/eye-to-hand configuration. This paper proposes a novel Kalman-filter-based...
Estimating the 3D shape information of a face from a single image is a challenging task, especially when the input image is captured under unconstrained scenarios (e.g., variations of pose, illumination, expression, or even disguise). Previous approaches to this problem typically require careful initialization, registration, or segmentation of the face image regions. With the objective to match the...
Collision accidents have become a crucial and urgent problem. Advanced Driver Assistance Systems (ADAS) can enhance traffic safety and improve efficiency. Toward this direction, we propose a robust low-cost system based on monovision to estimate the accurate 3D pose information of the target vehicles for further behavior prediction. Firstly, we combine the Haar features with AdaBoost classification...
We introduce and investigate several criteria for matching the outer contour generated by a model of the manipulation target against the image data captured with a stereo camera rig. The more complex criteria are intended for the initial stage of scene analysis, to provide pose and location estimation for path planning, and the faster methods can be used in real-time, e.g. for providing feedback during...
In this paper, we present an experimental analysis of how landmark distributions in a scene, as observed by a stereo-camera, affect Visual Odometry measurement performances. Translational and rotational tests have been performed in many different positions in an indoor environment. The Visual Odometry algorithm, which has been implemented firstly, guesses motion by a linear 3D-to-3D method embedded...
In this paper, a vision tracking system via color detection is presented. In this system, a monocular camera is used as a sensor to track and measure the relative pose of the target based on specified color detection with the help of four LED markers. Kalman filter is used in this system to predict the position of LED markers in the next frame of the camera image so as to decrease the area in which...
The authors have created a new color glove which has markers between the fingers and the palm or dorsal area, and have developed methods to eliminate border outlines caused between colored regions to make a natural finger outline extraction system. The authors select 6 colors used for markers and the positions of them. In the elimination process, outlines of marker regions' border are extracted. Elimination...
In this paper, we present the systematic design and implementation of a binocular vision-based measuring system for autonomous aerial refueling. The hardware configuration of the verification platform is presented, and vision algorithms including feature extraction and pose estimation are employed for estimating the relation between two rotorcrafts. To verify the autonomous aerial refueling of unmanned...
This paper represents research in progress in Simultaneous Localization and Mapping (SLAM) for Micro Aerial Vehicles (MAVs) in the context of rescue and/or recognition navigation tasks in indoor environments. In this kind of applications, the MAV must rely on its own onboard sensors to autonomously navigate in unknown, hostile and GPS denied environments, such as ruined or semi-demolished buildings...
In this paper, we propose a method for recognition and pose estimation of primitive shapes from depth images for spatial augmented reality (SAR). To use SAR in our everyday life, technology to recognize and estimate the pose of projected objects in the room is necessary. However, it is not a simple task to recognize primitive shapes because of their low 3D feature values.
In this work we present a technique for estimating the pose of an articulated object with only a simple shape model and no appearance model. We use a generative technique to propose, for a pair of stereo cameras, hypothesised correspondences for object pixels in two images. The feature space for each camera is a set of two-dimensional points, where each point consists of an intensity value and a flux...
Almost all robotics applications require accurate robot positioning. However, most of the developed methods lacks in ground truth reference to verify its accuracy relative to the real world. This paper proposes an effective vision based system to accurately track mobile robot's true position and orientation using multiple overhead cameras. This system is able to track and localize multiple mobile...
Real time 3D imaging applications such as on the fly 3D inspection or 3D reconstruction can be created by rigidly coupling a depth camera with an articulated measurement arm or a robot. For such applications, the “hand-eye transformation” between the depth camera and the measurement arm needs to be known. For depth cameras, the hand-eye transformation can either be estimated using 2D images or the...
Position and attitude estimation of helmet-mounted imaging devices e.g. camera/lidar is difficult in unstructured indoor environment due to lack of conventional localization systems, e.g. RF, Ultrasonic, UWB and Wi-Fi signals, usually available in modern office-like buildings. In this work, we use single MEMS IMU fitted on foot, which when combined with zero-velocity updates (ZUPT) in Extended Kalman...
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