In response to the inaccurate positioning of traditional camera relocation methods in scenes with large-scale or severe viewpoint changes, this study proposes a camera relocation method based on a cascaded graph neural network to achieve accurate sce...
Camera relocalization, a cornerstone capability of modern computer vision, accurately determines a camera’s position and orientation from images and is essential for applications in augmented reality, mixed reality, autonomous driving, delivery...
This paper presents an improved approach for scene-aware camera relocalization using RGB images and poses. Building upon the ACE network, we proposed a refined head structure that integrates skip and dense connections alongside channel attention mech...
Monocular camera relocalization recovers a six-degree-of-freedom pose from one RGB image, but direct absolute pose regression typically predicts translation and rotation from one terminal representation. We propose Decoupled SwinPose, a hierarchical...
Measurement of stress levels from an in-service structure can provide important and useful information regarding the current state of a structure. The stress relaxation method (SRM) is the most conventional and practical method, which has been widely...
The expansion of urban areas and associated clearing of habitat can have severe consequences for native wildlife. One option for managing wildlife in these situations is to relocate them. While there is a general perception that relocation is humane,...
This study introduces a visual SLAM real-time system designed for small indoor environments. The system demonstrates resilience against significant motion clutter and supports wide-baseline loop closing, re-localization, and automatic initialization....
As the global demand for surveillance cameras increases, the digital footage data also explicitly increases. Analyzing and extracting meaningful content from footage is a resource-depleting and laborious effort. The traditional video synopsis techniq...
To address the limitations of existing video anomaly detection methods that overly rely on pixel-space reconstruction and are sensitive to background noise and object scale variations, a self-supervised contrastive learning approach that integrates s...
The method of simultaneous localization and mapping (SLAM) using a light detection and ranging (LiDAR) sensor is commonly adopted for robot navigation. However, consumer robots are price sensitive and often have to use low-cost sensors. Due to the po...
Many visual SLAM systems are generally solved using natural landmarks or optical flow. However, due to textureless areas, illumination change or motion blur, they often acquire poor camera poses or even fail to track. Additionally, they cannot obtain...
The present study shows how Hungarian churches and religious communities responded to the physical closure and relocation to online spaces in the spring of 2020, since while physical gates became closed, digital gates became opened. In the churches,...
Dynamic environments are challenging for visual Simultaneous Localization and Mapping, as dynamic elements can disrupt the camera pose estimation and thus reduce the reconstructed map accuracy. To solve this problem, this study proposes an approach f...
Accurately estimating the pose of large arrays of fixed indoor cameras presents a significant challenge in computer vision, especially since traditional methods predominantly rely on overlapping camera views. Existing approaches for positioning non-o...
This paper presents a real-time object-based 3D change detection method that is built around the concept of semantic object maps. The algorithm is able to maintain an object-oriented metric-semantic map of the environment and can detect object-level...
Anthropomorphic robotic hands are designed to attain dexterous movements and flexibility much like human hands. Achieving human-like object manipulation remains a challenge especially due to the control complexity of the anthropomorphic robotic hand...
This paper proposes a novel multi-sensor-based indoor global localization system integrating visual localization aided by CNN-based image retrieval with a probabilistic localization approach. The global localization system consists of three parts: co...
While Low Emission Zone (LEZ) enforcement cameras provide a constant stream of traffic data, such resources remain significantly underexploited for urban mobility planning, as their current application is restricted to enforcing vehicle access regula...
This paper addresses appearance-based robot localization in 2D with a sparse, lightweight map of the environment composed of descriptor–pose image pairs. Based on previous research in the field, we assume that image descriptors are samples of a low-d...
Large sports stadiums require robust real-time monitoring due to high crowd density, complex spatial configurations, and limited network infrastructure. This research evaluates a hybrid edge–cloud architecture implemented in a national stadium...
Child-Robot Interaction (CRI) has become increasingly addressed in research and applications. This work proposes a system for emotion recognition in children, recording facial images by both visual (RGB—red, green and blue) and Infrared Thermal...
Complex environments pose great challenges for autonomous mobile robot navigation. In this study, we address the problem of autonomous navigation in 3D environments with staircases and slopes. An integrated system for safe mobile robot navigation in...
Insects play essential roles in ecosystems, providing services such as pollination and pest regulation. However, global insect populations are in decline due to factors like habitat loss and climate change, raising concerns about ecosystem stability....
Map-based, high-precision dynamic pose tracking and rapid relocalization in the case of unknown poses are very important for indoor navigation robots. This paper aims to propose a robust and high-precision indoor robot positioning algorithm that comb...
A camera-guided warehouse robot keeps its bearings by repeatedly estimating its pose against known visual references, and it must relocalize whenever that estimate is lost. What limits this process is often not identification but the availability of...
Cross-spectral local feature matching between visual and thermal images benefits many vision tasks in low-light environments, including image-to-image fusion and camera re-localization. An essential prerequisite for unleashing the potential of superv...
Augmented reality (AR) enhances the real world scene by overlaying virtual information onto it. Vision-based 3D tracking and registration is the key technology for ensuring the fusion of virtual and real content in monocular AR systems. Existing main...
The term “mechanical neck pain” is a generic term used to define neck pain in people with neck injuries, neck dysfunction, or shoulder and neck pain. Several factors must be considered during the physical-therapy evaluation of cervical di...
Visual Simultaneous Localization and Mapping (SLAM) approaches have achieved a major breakthrough in recent years. This paper presents a new monocular visual odometry algorithm able to localize in 3D a robot or a camera inside an unknown environment...
This article rereads Akira Kurosawa’s 1960 film The Bad Sleep Well as a modern Hamlet that relocates Shakespeare’s crisis of action from dynastic succession to postwar bureaucratic and corporate modernity. It shifts attention away from pl...
Lateral flow immunoassays for detecting biomarkers in body fluids are simple, quick, inexpensive point-of-care tests widely used in disease surveillance, such as during the coronavirus disease 2019 (COVID-19) pandemic. Improvements in sensitivity wou...
To protect our planet, the material recycling of domestic waste is necessary. Since the COVID-19 pandemic began, the volume of domestic waste has surged overwhelmingly, and many countries suffered from poor waste management. Increased demand for food...
The capability of low-cost photogrammetric systems to provide live six degrees of freedom (6DoF) tracking of multiple objects offers great value in providing high-quality and consistent part production by automated manufacturing systems. However, mon...
All associations use on-premises data focus. An on-premises data focus suggests that an association maintains all locally required IT systems. An on-premises data focus consolidates everything from the servers that support Web and email access to the...
Most indoor environments have wheelchair adaptations or ramps, providing an opportunity for mobile robots to navigate sloped areas avoiding steps. These indoor environments with integrated sloped areas are divided into different levels. The multi-lev...
Vision-only driving perception systems are highly sensitive to illumination variations, particularly under low-light conditions where reduced contrast and structural degradation impair detection and segmentation accuracy. Rather than treating enhance...
Dexterous object manipulation using anthropomorphic robot hands is of great interest for natural object manipulations across the areas of healthcare, smart homes, and smart factories. Deep reinforcement learning (DRL) is a particularly promising appr...
In surface mining, rockfall can seriously threaten the safety of personnel located at the base of highwalls and cause serious damage to equipment and machinery. Close-range photogrammetry for the continuous monitoring of rock surfaces represents a va...
Thermal refuges are becoming increasingly influential for dictating the population status and spatial distribution of cold-water stenotherm salmonids in the mid- to southern extent of their range. The global climate is predicted to continue to warm,...