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The automatic detection of anomalies in Active and Assisted Living (AAL) environments is important for monitoring the wellbeing and safety of the elderly at home. The integration of smart domotic sensors (e.g. presence detectors) and those ones equipping modern mobile robots (e.g. RGB-D cameras) provides new opportunities for addressing this challenge. In this paper, we propose a novel solution to...
A collision detection system triggering on human motion was developed using the Robot Operating System (ROS) and the Point Cloud Library (PCL). ROS was used as the core of the programs and for the communication with an industrial robot. Combining the depths fields from the 3D cameras was accomplished by the use of PCL. The library was also the underlying tool for segmenting the human from the registrated...
Due to variations in pose and illumination condition, the appearance of can be significantly different in different cameras and the performance of person re-identification is degraded. In this paper, a person re-identification based on multi-level and multi-feature fusion for this phenomenon is proposed. Firstly, we divided each sample into three parts and multi-layer sampling. Secondly, we extracted...
This study proposes a method for analysis and calibration of the geo-coding error in mapping of the moving targets, 'movers', detected in the Wide Area Motion Imagery (WAMI). To estimate the accurate position of the movers, an iterative Ordinary Least Squares (OLS) optimisation of the camera model parameters is performed. The OLS is set to minimise the Euclidean distance between the locations of the...
This paper addresses the problem of controlling the posture of a dual wheeled mobile terrestrial robot, with movement constraints with the objective of detect and follow a planar moving target, using a single fixed vision sensor. The main challenge addressed is to keep the robot oriented in the same direction as the target. In order to accomplish it, a computationally simple control algorithm is proposed...
Automated inspection of apples requires that the entire surface of the fruit passes through the view of at least one camera. This work uses Monte Carlo simulation to investigate the extent of coverage of the apple surface when viewed by three four and five cameras arranged in a plane. Each camera has a circular inspection area that is 45 to 50% of the apple size. The number of images per apple rotation...
Robots assist rescuers in search and rescue operations. The important aspects investigated in this study are the integration of a mechatronic system that will allow for a robotic platform with a vision system. The research collaboration between Argentina and South Africa is discussed with the correlating research areas that each country will investigate to allow for the development and advancement...
In supervised machine learning applications, a data set of training and validation features and labels is required to train a neural network. In this paper, we present a remote-controlled, mobile robot and describe software used to generate a data set for vision-based, supervised machine learning applications. We present results from an experiment, which validates the developed platform, and also...
Stixel-based segmentation is specifically designed towards obstacle detection which combines road surface estimation in traffic scenes, stixel calculations, and stixel clustering. Stixels are defined by observed height above road surface. Road surfaces (ground manifolds) are represented by using an occupancy grid map. Stixel-based segmentation may improve the accuracy of real-time obstacle detection,...
Consumer-grade RGB-D cameras capture RGB images along with per-pixel depth information, and because of their limited cost and ability to measure distances at a high frame rate, have been used in robotics and computer vision application. However, drawbacks include the repeatability and accuracy of RGB-D cameras for object detection and localization. This paper investigates and compares RGB-D cameras'...
In this work, several state-of-the-art Blind Image Quality Assessment (IQA) metrics and measures are evaluated in order to verify how they behave on extreme conditions such as the ones found on pictures of metallic surfaces. This is an important research topic given that the automation of the image acquisition comprehends one of the essential steps towards the automation and autonomy in many fields...
This paper presents a fusion of monocular camera-based metric localization, IMU and odometry in dynamic environments of public roads. We build multiple vision-based maps and use them at the same time in localization phase. For the mapping phase, visual maps are built by employing ORB-SLAM and accurate metric positioning from LiDAR-based NDT scan matching. This external positioning is utilized to correct...
In object tracking field, occlusion situations between objects are important factors that degrade the performance of tracking algorithms. In this paper, we present a track management method in the tracking level to solve the discontinuous tracking problem caused by occlusions between detected objects. This work is performed by predicting the occlusion situation between detected objects and managing...
While current implementations of LIDAR-based autonomous driving systems are capable of road following and obstacle avoidance, they are still unable to detect road lane markings, which is required for lane keeping during autonomous driving sequences. In this paper, we present an implementation of semantic image segmentation to enhance a LIDAR-based autonomous ground vehicle for road and lane marking...
The conventional control method for road-heating systems, which is controlled mainly by snowfall, is the feedforward control. Therefore, the road-heating systems often operate in spite of no snow on the parking lots. In this paper, we introduce the method of feedback control for road-heating systems that detects snow condition on the parking lots, and turns road-heating systems on and off properly...
Currently, the prediction of fish species and catches is based on the experience of fishermen. Echo sounders can support fisheries; however, they cannot identify fish species. A system for the identification of fish species with machines has not been established. The purpose of this research is to propose a new method for the identification of fish species using echo sounders attached to a set-net...
Mobile robot localization has been considered to be an important task in the field of robotics research. It is known that it is difficult to estimate the self-position in dynamic environments where the positions of objects used as landmarks change. In this paper, we propose a robust method to estimate self-position from the first person view captured by a camera on a robot using Recurrent Convolutional...
The “Digital race — Driverless car” was a student competition where each team was given a model car with fixed specification in both mechanical and electronics. The mission was to program the car to run automatically in the condition of road having obstacles, missing lane lines and bridges with completely out lane lines in the field of view. This paper aims to address the issues facing in the competition...
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...
Vision is a potent source of information, not just for humans, but for robots as well. Processing visual information is a computationally expensive task, one that is often difficult to accomplish in real-time on embedded hardware. In the broad field of visual research exists egomotion estimation, the process of determining self-motion from optical flow. Here we show a technological adaptation and...
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