Results 141 to 150 of about 103,598 (304)

DiffusionTrack: Diffusion Model for Multi-Object Tracking

open access: yesProceedings of the AAAI Conference on Artificial Intelligence
Multi-object tracking (MOT) is a challenging vision task that aims to detect individual objects within a single frame and associate them across multiple frames. Recent MOT approaches can be categorized into two-stage tracking-by-detection (TBD) methods and one-stage joint detection and tracking (JDT) methods.
Run Luo   +5 more
openaire   +2 more sources

Multimodal Perception and Machine Learning‐Empowered Human Machine Interfaces With Double‐Network Hydrogel Fibers

open access: yesAdvanced Functional Materials, EarlyView.
This work develops polyacrylamide‐alginate (PAM‐Alg) double‐network hydrogel fibers for multimodal perception and intelligent human‐machine interfaces. The covalent‐ionic network provides high strength, toughness, and stable conductivity. Easily woven into wearables and integrated with soft robots, the fibers enable object and temperature recognitions ...
Yujue Yang   +10 more
wiley   +1 more source

Algorithms for multi-modal human movement and behaviour monitoring

open access: yes, 2011
This thesis describes investigations into improvements in the field of automated people tracking using multi-modal infrared (IR) and visible image information.
Townsend, JS
core  

EF-StrongSORT: An Enhanced Feature StrongSORT Model for Multi-Object Tracking

open access: yesIEEE Access
Multi-object tracking (MOT) faces persistent challenges owing to the complexities introduced by occlusions, dynamic appearance variations, and the rapid motion of objects within a scene.
Miar Mamdouh Khalil   +3 more
doaj   +1 more source

A Skin‐Like Strain Sensor for Real‐Time Human Motion Detection

open access: yesAdvanced Functional Materials, EarlyView.
A skin‐like strain sensor with exceptional flexibility and breathability enables real‐time human motion detection. It offers continuous ECG monitoring and gesture recognition, ensuring high durability and comfort. This innovative design is ideal for wearable applications, combining reliable performance with seamless integration into dynamic ...
Shiqi Song   +5 more
wiley   +1 more source

Robust Tracking in Aerial Imagery Based on an Ego-Motion Bayesian Model

open access: yes, 2010
A novel strategy for object tracking in aerial imagery is presented, which is able to deal with complex situations where the camera ego-motion cannot be reliably estimated due to the aperture problem (related to low structured scenes), the strong ego ...
Narciso García   +5 more
core   +1 more source

Digitizing the Filtration Interface: A Smart, Modular Janus Wood Platform for Self‐Reporting Oil/Water Remediation

open access: yesAdvanced Functional Materials, EarlyView.
This work developed a smart Janus wood membrane integrating asymmetric wettability with built‐in electrical sensing for oil‐water separation. The membrane achieved > 99.5% separation efficiency and high flux by leveraging wood's natural anisotropic pore structure.
Kaiwen Chen   +10 more
wiley   +1 more source

Pickering‐Engineered Microparticles for Magnetically Guided Motion and Light‐Triggered Catalysis

open access: yesAdvanced Functional Materials, EarlyView.
Magnetically responsive wax microparticles stabilized by hematite cubes through the Pickering emulsification strategy are developed, showing controlled size, motion, and light‐activated catalytic activity. Annealing under a magnetic field enhances their mobility and steering.
Chiara Ferlito   +6 more
wiley   +1 more source

DESIGN AND IMPLEMENTATION OF AN OBJECT TRACKING SYSTEM CONTROL USING PID AND MOVEMENT PREDICTION

open access: yes, 2009
The tracking system usually has some lack of problem, that is unstable system when the object moved so the tracking process can’t define the object position well. On the other hands, when the object moves, the system can’t track object suddenly along
Ningrum, Endah S
core  

A convolution particle filtering approach for tracking elliptical extended objects [PDF]

open access: yes, 2013
This paper proposes a convolution particle filtering approach for extended object tracking. Convolution particle filters (CPFs) are likelihood free filters. They are based on convolution kernel probability density representation.
Gning, Amadou   +3 more
core  

Home - About - Disclaimer - Privacy