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An automated docking system is presented for an autonomous underwater vehicle utilizing light-field imaging for navigation guidance. This article focuses on three major components of the system: docking position acquisition with light-field imaging, optimal docking trajectory planning, and nonlinear trajectory tracking control. With the camera sensor data of each photographic exposure, depth maps...
This paper deals with automatic estimation of the horizon in videos from fixed surveillance cameras. The proposed algorithm is fully automatic in the sense that no user input is needed per-camera and it works with various scenes (indoor, outdoor, traffic, pedestrian, livestock, etc.). The algorithm detects moving objects, tracks them in time, assesses some of their geometric properties related to...
Obstacle detection and tracking is a fundamental task for several Advanced Driver Assistance Systems (ADAS) and self-driving cars. Several approaches have been presented in the literature in the last years and many of them are based on visual sensors. In this paper we propose an approach that uses only stereo cameras to detect and track obstacles and compute visual odometry to get the vehicle's ego-velocity...
Due to the sparse distribution of road video surveillance cameras, precise trajectory tracking for hit-and-run vehicles remains a challenging task. Previous research on vehicle trajectory recovery mostly focuses on recovering trajectory with low-sampling-rate GPS coordinates by retrieving road traffic flow patterns from collected GPS information. However, to the best of our knowledge, none of them...
ORB-SLAM2 is one of the better-known open source SLAM implementations available. However, the dependence of visual features causes it to fail in featureless environments. With the present work, we propose a new technique to improve visual odometry results given by ORB-SLAM2 using a tightly Sensor Fusion approach to integrate camera and odometer data. In this work, we use odometer readings to improve...
Lane estimation plays a central role for Driver Assistance Systems, therefore many approaches have been proposed to measure its performance. However, no commonly agreed metric exists. In this work, we first present a detailed survey of the current measures. Most of them apply pixel-level benchmarks on camera images and require a time-consuming and fault-prone labeling process. Moreover, these metrics...
Viewpoint variation is a major challenge in video- based human action recognition. We exploit the simultaneous RGB and Depth sensing of RGB-D cameras to address this problem. Our technique capitalizes on the complementary spatio-temporal information in RGB and Depth frames of the RGB-D videos to achieve viewpoint invariant action recognition. We extract view invariant features from the dense trajectories...
Motion vectors extracted from a compressed video file can be used to track objects in the video and it could be efficient as motion vectors provide trajectory information of the objects. However, tracking objects represented by the motion vectors can be inaccuracy because of camera movement, small size sets of motion vectors acting as noise, unmoving of the object and occlusion. These are conditions...
This paper proposes a system for caring a physically impaired person by a mobile robot employing cooperative object recognition. It is a well-known fact that object recognition is not an easy task for a robot particularly in a real environment. It is, on the contrary, easy for a human. In the proposed system, a mobile robot goes to a spot where a user wishes to go in place of him/her and transfers...
In this paper, based on quaternion and Euler angles, an attitude control algorithm is proposed for pitching and rolling of quadrotor aircraft. In addition, the target tracking algorithm of quadrotor aircraft is designed by using the collected video information and color feature recognition. The system is based on the homemade quadrotor aircraft, using gyroscope, accelerometer as the original measurement...
We address the problem of incrementally modeling and forecasting long-term goals of a first-person camera wearer: what the user will do, where they will go, and what goal they seek. In contrast to prior work in trajectory forecasting, our algorithm, DARKO, goes further to reason about semantic states (will I pick up an object?), and future goal states that are far in terms of both space and time....
This work presents a mixed reality environment for orthopaedic interventions that provides a 3D overlay of Cone-beam CT images, surgical site, and real-time tool tracking. The system uses an RGBD camera attached to the detector plane of a mobile C-arm, which is a typical device to acquire X-Ray images during surgery. Calibration of the two devices is done by acquiring simultaneous CBCT and RGBD scans...
Collaboration between heterogeneous robots can greatly improve the overall robot system by obtaining capabilities that each single robot is unable to achieve. In this paper, we present a collaborative robot system designed for search and rescue missions in an unknown environment with obstacles. The system consists of an aerial robot and a ground robot. An extended Kalman filter (EKF) is used for...
We present a quadrotor system capable of autonomously landing on a moving platform using only onboard sensing and computing. We rely on state-of-the-art computer vision algorithms, multi-sensor fusion for localization of the robot, detection and motion estimation of the moving platform, and path planning for fully autonomous navigation. Our system does not require any external infrastructure, such...
This paper presents a self-memory prediction model to mitigate the effects of image based visual servoing (IBVS) system under uncertainty. The performance of IBVS system is easily influenced by different tasks, diverse environments and uncertain disturbances. Through building a self-memory prediction model to keep previous movement tendency in the every current movement, the framework of a self-memory...
Feature extraction is a key component of a Monocular Simultaneous Localization and Mapping (Monocular SLAM) system which permits to extract features and can also reliably track them over frames. In this paper, a novel approach for Monocular SLAM is proposed. This approach uses the information on the camera displacement and image saliency to adequately extract stable and suitable features, ones that...
We show that walls, and other obstructions with edges, can be exploited as naturally-occurring “cameras” that reveal the hidden scenes beyond them. In particular, we demonstrate methods for using the subtle spatio-temporal radiance variations that arise on the ground at the base of a wall's edge to construct a one-dimensional video of the hidden scene behind the wall. The resulting technique can be...
Fully automated vehicles and mobile robots operate in a shared environment with pedestrians. To minimize the risk for pedestrians, it is very important to track them in a precise way. As cameras are often installed in surveillance situations, they are used for tracking pedestrians in a shared environment. To improve the accuracy of the tracking, it is necessary to include all available context information...
This paper explores the predictive power of perhaps the most well-supported human performance model in the context of a complex ecological task. The model is Fitts Law, which describes the classic speed-accuracy tradeoff of goal-directed motor behavior. The task is modern pistol shooting competition, which demands explicit cognitive strategy and full-body biomechanical coordination. Data obtained...
This paper presents a new approach for navigating a quadrotor over undulated terrains that can be of great importance for the use of unmanned aerial vehicles in civilian applications such as monitoring of pipes, bridges and buildings. The proposed approach involves the use of a single-beam LiDAR to estimate the terrain profile under uncertainty. The LiDAR is installed at the base of a quadrotor and...
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