Unsupervised learning has shown immense potential in object tracking, where accurate classification and regression are crucial for unsupervised trackers. However, the classification and regression branches of most unsupervised trackers calculate obje...
Scene sonification is a powerful technique to help Visually Impaired People (VIP) understand their surroundings. Existing methods usually perform sonification on the entire images of the surrounding scene acquired by a standard camera or on the prior...
This research presents the development of a novel object detection algorithm designed to identify humans in natural outdoor environments using minimal computational resources. The proposed system, SARGAS, combines a custom convolutional neural networ...
3D object detection and tracking technology are increasingly being adopted in unmanned ground vehicles, as robust perception systems significantly improve the obstacle avoidance performance of a UGV. However, most existing algorithms depend heavily o...
A novel video object segmentation algorithm, which segments out multiple objects in a video sequence in unsupervised or weakly supervised manners, is proposed in this work. First, we match visually important object instances to construct salient obje...
In this paper we present a novel unsupervised approach to detecting and segmenting objects as well as their constituent symmetric parts in an image. Traditional unsupervised image segmentation is limited by two obvious deficiencies: the object detect...
The use of eye tracking technology, together with other physiological measurements such as psychogalvanic skin response (GSR) and electroencephalographic (EEG) recordings, provides researchers with information about users’ physiological behavio...
Motion perception is a fundamental function of biological visual systems, enabling organisms to navigate dynamic environments, detect threats, and track moving objects. Inspired by the mechanisms of biological motion processing, we propose an Unsuper...
Multi-object tracking aims to assign a uniform ID for the same target in continuous frames, which is widely used in autonomous driving, security monitoring, etc. In the previous work, the low-scoring box, which inevitably contained occluded target, w...
Hand tracking in video is an increasingly popular research field due to the rise of novel human-computer interaction methods. However, robust and real-time hand tracking in unconstrained environments remains a challenging task due to the high number...
To meet the challenge of video target tracking, based on a self-organization mapping network (SOM) and correlation filter, a long-term visual tracking algorithm is proposed. Objects in different videos or images often have completely different appear...
The high operational velocities of high-speed trains present constraints on their onboard track intrusion detection systems for real-time capture and analysis, encompassing limited computational resources and motion image blurring. This emphasizes th...
Background/Objectives: Children with autism spectrum disorder (ASD) often exhibit differences in attention regulation and visual behavior. However, many ASD eye-tracking datasets lack reliable moment-to-moment behavioral or emotional annotations, lim...
Video cameras are one of the important elements in ensuring security in public areas. Videos inspected by expert personnel using traditional methods may have a high error rate and take a long time to complete. In this study, a new deep learning-based...
Remote sensing techniques have been shown effective for large-scale damagesurveys after a hazardous event in both near real-time or post-event analyses. The paperaims to compare accuracy of common imaging processing techniques to detect tornadodamage...
High-resolution automotive radar sensors play an increasing role in detection, classification and tracking of moving objects in traffic scenes. Clustering is frequently used to group detection points in this context. However, this is a particularly c...
Indoor localization has long been a challenging task due to the complexity and dynamism of indoor environments. This paper proposes ULG-SLAM, a novel unsupervised learning and geometric-based visual SLAM algorithm for robot localizability estimation...
Background/Objectives: Digital health applications (DHAs) promise to improve disease self-management, but adherence remains suboptimal. We aimed to explore self-monitoring practices of rheumatic and musculoskeletal diseases (RMD) patients. A web-surv...
This paper has two objectives: the first is to generate two binary flags to indicate useful frames permitting the measurement of cardiac and respiratory rates from Ballistocardiogram (BCG) signals—in fact, human body activities during measurements ca...
In previous works, we have shown the efficacy of using Deep Belief Networks, paired with clustering, to identify distinct classes of objects within remotely sensed data via cluster analysis and qualitative analysis of the output data in comparison wi...
Object tracking requires heterogeneous images that are well registered in advance, with cross-modal image registration used to transform images of the same scene generated by different sensors into the same coordinate system. Infrared and visible lig...
Single sensor systems and standard optical—usually RGB CCTV video cameras—fail to provide adequate observations, or the amount of spectral information required to build rich, expressive, discriminative features for object detection and tr...
A critical issue in image analysis for analyzing animal behavior is accurate object detection and tracking in dynamic and complex environments. This study introduces a novel preprocessing algorithm to bridge the gap between computational efficiency a...
Almost all vision technologies that are used to measure traffic volume use a two-step procedure that involves tracking and detecting. Object detection algorithms such as YOLO and Fast-RCNN have been successfully applied to detecting vehicles. The tra...
Radar systems are mainly used for tracking aircraft, missiles, satellites, and watercraft. In many cases, information regarding the objects detected by a radar system is sent to, and used by, a peripheral consuming system, such as a missile system or...
Recent developments in computer vision have significantly enhanced the automation and objectivity of sports analytics. This paper proposes a novel deep learning-based framework for estimating football possession directly from broadcast video, elimina...
In two-color multiview (2CMV) advanced geospatial information (AGI) products, temporal changes in synthetic aperture radar (SAR) images acquired at different times are detected, colorized, and overlaid on an initial image such that new features are r...
The importance of sustainable development has risen in recent years due to the significant number of people affected by lack of access to essential resources as well as the need to prepare for and adapt to intensifying climate change and rapid urbani...
Falls are a leading cause of paediatric injuries, yet school-based prevention relies heavily on subjective observation rather than objective biomechanical assessment. This paper introduces the Safe Fall framework, integrating a judo-inspired educatio...
The use of advanced learning technologies (ALT) techniques in learning management systems (LMS) allows teachers to enhance self-regulated learning and to carry out the personalized monitoring of their students throughout the teaching–learning process...
In livestock breeding, continuous and objective monitoring of animals is manually unfeasible due to the large scale of breeding and expensive labour. Computer vision technology can generate accurate and real-time individual animal or animal group inf...
Drowning remains the third leading cause of accidental injury-related deaths worldwide, disproportionately affecting low- and middle-income countries where lifeguard coverage is limited or absent. To address this critical gap, we present Robobuoy, an...
The foreground segmentation method is a crucial first step for many video analysis methods such as action recognition and object tracking. In the past five years, convolutional neural network based foreground segmentation methods have made a great br...
Access to healthcare, including physiotherapy, is increasingly occurring through virtual formats. At-home adherence to physical therapy programs is often poor and few tools exist to objectively measure participation. The aim of this study was to deve...
Offshore wind development in the Colombian Caribbean requires characterization of tropical cyclone exposure to support climate-resilient planning, yet objective regime classifications for this basin remain limited. This study develops an unsupervised...
Go-arounds are a necessary aspect of commercial aviation and are conducted after a landing attempt has been aborted. It is necessary to conduct go-arounds in the safest possible manner, as go-arounds are the most safety-critical of operations. Recent...
An accelerating trend of global urbanization accompanying population growth makes frequently updated land use and land cover (LULC) maps critical. LULC maps have been widely created through the classification of remotely sensed imagery. Maps of urban...
Using deep learning to improve the capabilities of high-resolution satellite images has emerged recently as an important topic in automatic classification. Deep networks track hierarchical high-level features to identify objects; however, enhancing t...
28 September 2022
Background: Children’s access to non-school destinations is important for their well-being, but this has been overlooked in transport planning. Research on children’s access to non-school destinations is growing, and there is a need for a...
New technologies for monitoring grip forces during hand and finger movements in non-standard task contexts have provided unprecedented functional insights into somatosensory cognition. Somatosensory cognition is the basis of our ability to manipulate...
Background and Objectives: Real-world persistence with medication-supported weight management programs is often low. While digital weight loss services (DWLS) provide multi-modal digital supports to improve engagement and counter attrition, the exist...