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We present in this paper a novel warehouse inventory scheme. The main purpose of this work is to make the inventory process completely autonomous. To this end, an Unmanned Ground Vehicle (UGV) and an Unmanned Aerial Vehicle (UAV) work cooperatively. The UGV is used as the carrying platform, and considered as a ground reference for the indoor flight of the UAV. While the UAV is used as the mobile scanner...
This paper proposes a method of rotation estimation of a fast spinning marker-less golf ball, which rotates up to 60 degrees in a 1-millisecond frame, from two consecutive frames of an infrared video sequence. The proposed method solely relies on the dimple pattern, which has slight irregularity in its configuration providing a clue for alignment, and does not need help of logo marks or fiducial markers...
In this study, model-referenced pose estimation using monocular vision is applied to the navigation of an underwater vehicle in an underwater environment. The relative spatial information between the vehicle and the nearby underwater structure is obtained by employing 3D model-referenced tracking techniques. The obtained relative pose enables the underwater robot to localize around the underwater...
Over the last decade, there have been many studies that focus on modeling driver behavior, and in particular detecting and overcoming driver distraction in an effort to reduce accidents caused by driver negligence. Such studies assume that the entire onus of avoiding accidents are on the driver alone. In this study, we adopt a different stance and study the behavior of pedestrians instead. In particular,...
This paper introduces a fiducial marker which favours accuracy over run-time performance. Its intended use is for creating ground truth for outdoor SLAM in GPS-denied environments. Rather than using only corners or edges for pose estimation, the marker has a radial sinusoid pattern which has a predictable appearance under perspective projection. A non-linear optimisation routine estimates the marker's...
In this paper we present a new 3D line alignment technique that can be used in limited resourced MAVs for performing loop closures as well as mutual localisation between MAVs. We identify pairs of 3D line matches from RGB-D frames and find the optimal transformation which aligns these two line sets onto each other in order to find the corresponding relative pose. The alignment of the two 3D line sets...
We propose an approach for emptying of bin using a combination of Image and Range sensor. Offering a complete solution: calibration, segmentation and pose estimation, along with approachability analysis for the estimated pose. The work is novel in the sense that the objects to be picked are featureless and uniformly black in colour, hence existing approaches are not directly applicable. A key point...
We present an architecture for online, incremental scene modeling which combines a SLAM-based scene understanding framework with semantic segmentation and object pose estimation. The core of this approach comprises a probabilistic inference scheme that predicts semantic labels for object hypotheses at each new frame. From these hypotheses, recognized scene structures are incrementally constructed...
We present a framework for vision based localization for two or more multirotor aerial vehicles relative to each other. This collaborative localization technique is built upon a relative pose estimation strategy between two or more cameras with the capability of estimating accurate metric poses between each other even through fast motion and continually changing environments. Through synchronized...
Self-localization using visual markers is widely used for precise control of Unmanned aerial vehicles (UAVs). This paper presents a novel method of 6-DoF pose estimation using a monocular camera and non co-planar markers. We conducted numerical simulations comparing pose estimation using co-planar markers and using non co-planar markers, and designed a non co-planar marker feasible for robotics applications...
The objective of this work is to estimate 3D human pose from a single RGB image. Extracting image representations which incorporate both spatial relation of body parts and their relative depth plays an essential role in accurate3D pose reconstruction. In this paper, for the first time, we show that camera viewpoint in combination to 2D joint locations significantly improves 3D pose accuracy without...
In this paper, we present a novel, general, and efficient architecture for addressing computer vision problems that are approached from an 'Analysis by Synthesis' standpoint. Analysis by synthesis involves the minimization of reconstruction error, which is typically a non-convex function of the latent target variables. State-of-the-art methods adopt a hybrid scheme where discriminatively trained predictors...
We propose a deep convolutional neural network for 3Dhuman pose and camera estimation from monocular imagesthat learns from 2D joint annotations. The proposed networkfollows the typical architecture, but contains an additionaloutput layer which projects predicted 3D joints onto2D, and enforces constraints on body part lengths in 3D.We further enforce pose constraints using an independentlytrained...
Localization systems for mobile robots are a trade-off between accuracy, robustness and costs. Current solutions for landmark based indoor localization are either expensive or inaccurate and unreliable. Accurate solutions for instance require costly infrastructure and/or high computational power. Additionally, self-balancing robots have particular challenges due to the unstable nature of the system...
In the Unmanned Air Vehicle (UAV) navigation the main challenge is estimating and maintaining the accurate values of UAVs position and orientation. The onboard Inertial Measurement Unit (IMU) provide the measurements but it is mainly affected from the accumulated error due to drift in measurements. Traditionally the Global Position System (GPS) measurements of vehicles position data can be fused with...
Human pose estimation is an important research topic in the field of computer vision. Pose recognition is widely used in human-computer interaction, games, security, telepresence, medical and other fields. There has been some scholars put forward many new methods on this issue. But due to the quality differences between imaging devices, complicated appearance of characters, changeable body posture,...
In this paper, a feasibility study is conducted to estimate the pose of a vehicle based on a mono-camera using road direction signs and a public online database. The proposed algorithm uses a mono-camera to detect and segment the road direction sign and matches the detected sign image with the reference image in the database to calculate the relative pose between the road sign and the vehicle. Using...
Augmented Reality (AR) is currently gaining popularity in multiple professional use cases. However, applying AR for outdoor environments is still very difficult, especially when targeting customer-grade mobile devices. This paper presents extensions to a previous panoramic tracking algorithm, which is a visual tracking method for unprepared outdoor use cases. The panorama tracker is extended by Unity3D...
The current paper is dealing with the use of a novel system that takes advantage of several sensors (Global Navigation Satellite System-GNSS, Inertial Measurement Units-IMU and Digital Imaging Sensors — DIS) that are integrated on a single platform to visualize and provide augmented pictures of underground infrastructure networks (electricity, water, district heating, irrigation, sewerage and communication...
Human pose estimation is a well-known computer vision problem that receives intensive research interest. The reason for such interest is the wide range of applications that the successful estimation of human pose offers. Articulated pose estimation includes real time acquisition, analysis, processing and understanding of high dimensional visual information. Ensemble learning methods operating on hand-engineered...
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