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Augmented Reality (AR) introduces vast opportunities to the industry in terms of time and therefore cost reduction when utilized in various tasks. The biggest obstacle for a comprehensive deployment of mobile AR is that current devices still leave much to be desired concerning computational and graphical performance. To improve this situation in this paper we introduce an AR Edge Computing architecture...
Recently, smart phones are usually equipped with cameras and motion sensors. This means that mobile phones have become good platforms to deploy augmented reality (AR) applications. We propose a new tracking system for AR which uses inertial measurement units (gyroscope, accelerometer and magnetic field sensor) combined with a camera to automatically detect and track a dominant plane in the scene without...
In this paper we present an augmented reality binocular system to allow long range high precision augmentation of live telescopic imagery with aerial and terrain based synthetic objects, vehicles, people and effects. The inserted objects must appear stable in the display and must not jitter and drift as the user pans around and examines the scene with the binoculars. The design of the system is based...
We present a new formulation for pose estimation using an extended Kalman filter that takes advantage of the Lie group structure of rotations. Using the exponential map along with linearized rotations for updates and errors permits a graceful filter formulation that avoids the awkward representation of Euler angles and the required norm constraint for quaternions. We demonstrate this approach with...
It is well known in a Bayesian filtering framework, the use of inertial sensors such as accelerometers and gyroscopes improves 3D tracking performance compared to using camera measurements only. The performance improvement is more evident when the camera undergoes a high degree of motion. However, it is not well known whether the inertial sensors should be used as control inputs or as measurements...
A novel camera pose tracking system using a stochastic inertial-visual sensor fusion has been proposed. A method based on the Particle Filtering concept has been adapted for inertial and vision data fusion, which benefits from the agility of inertial-based tracking and robustness of vision-based camera tracking.
This paper presents a new intuitive method for robot tool path teaching in Augmented Reality (AR) environment. Conventional industrial robot teaching method is long known to be either tedious or require a highly accurate virtual representation of robot work cell. Our method targets to provide the user with a fast and easy way of programming an industrial robot for useful tasks in a safe environment...
The estimation of a camera's egomotion is a highly desireable goal in many different application fields such as augmented reality (AR), visual navigation, robotics or entertainment. Especially for real-time modeling the former estimation of the camera trajectory is an elementary step towards the generation of three dimensional scene models. This paper presents a framework for simultaneous recovery...
In this paper, we present a novel approach for mobile augmented reality system. We estimate the 3D camera pose by detecting local invariant image features and combining them with the camera's accelerometer data. We applied NELFD - Neuroevolved Local Feature Descriptor that encodes data around points of interest in the image using a neural network with evolved topology and weights. For every image...
The task of vision based people tracking is a major research problem in the context of surveillance applications or human behavior estimation, but it has had only minimal impact on (Ubiquitous) Augmented Reality applications thus far. Deploying stationary infrastructural cameras within indoor environments for the purpose of Augmented Reality could provide a users' devices with additional functionality...
Visual simultaneous localisation and mapping (SLAM) is since the last decades an often addressed problem. Online mapping enables tracking in unknown environments. However, it also suffers from high computational complexity and potential drift. Moreover, in augmented reality applications the map itself is often not needed and the target environment is partially known, e.g. in a few 3D anchor or marker...
In this paper we present an efficient algorithm for estimating the 3D localization in an urban environments by fusing measurements from GPS receiver, inertial sensor and vision. Such hybrid sensor is important for numerous applications including outdoor mobile augmented reality and 3D robot localization. Our approach is based on non-linear filtering of these complementary sensors using a multi-rate...
Flight cockpit head tracking system is an important impetus for head pose tracking in fields of virtual or augmented reality. This paper presents a novel approach to dynamically track pilot's head pose using sensor fusion. The proposed approach utilizes a sensor fusion framework, composed of extended Kalman filters (EKF) and fusion filters (FF), to fuse poses from an inside-out tracking (IOT) and...
In this paper we present a multi sensor concept for localization and augmented-reality visualization of backscatter RFID tags. The sensor data of a camera and a RFID FMCW reader system are combined based on a synthetic aperture radar principle. The system enables the localization of tagged goods without the use of any installed infrastructure. We integrate a FMCW RFID reader and a camera system into...
Accurate head pose tracking is a key issue for indoor augmented reality systems. This paper proposes a novel approach to track head pose of indoor users using sensor fusion. The proposed approach utilizes a track-to-track fusion framework composed of extended Kalman filters and fusion filter to fuse the poses from the two complementary tracking modes of inside-out tracking (IOT) and outside-in tracking...
Ubiquitous tracking (Ubitrack) setups, consisting of many previously unknown sensors, offer many possibilities to perform sensor fusion in order to increase robustness and accuracy. In particular, the dynamic combination of mobile and stationary trackers enables the creation of new wide-area tracking concepts. In this work, we present a setup in which a gyroscope is dynamically fused with three different...
We review some recent techniques for 3D tracking and occlusion handling for computer vision-based augmented reality. We discuss what their limits for real applications are, and why object recognition techniques are certainly the key to further improvements.
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