scholarly journals Real-time video tracking using PTZ cameras

2003 ◽  
Author(s):  
Sangkyu Kang ◽  
Joon-Ki Paik ◽  
Andreas Koschan ◽  
Besma R. Abidi ◽  
Mongi A. Abidi
Keyword(s):  
Real Time ◽  
Video Tracking

scholarly journals Digital dynamic discrimination of primary colorectal cancer using systemic indocyanine green with near-infrared endoscopy

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jeffrey Dalli ◽  
Eamon Loughman ◽  
Niall Hardy ◽  
Anwesha Sarkar ◽  
Mohammad Faraz Khan ◽  
...  
Keyword(s):  
Indocyanine Green ◽  
Real Time ◽  
Normal Tissue ◽  
Near Infrared ◽  
Malignant Lesion ◽  
Fluorescence Analysis ◽  
Video Tracking ◽  
Continuous Stream ◽  
Rich Data

AbstractAs indocyanine green (ICG) with near-infrared (NIR) endoscopy enhances real-time intraoperative tissue microperfusion appreciation, it may also dynamically reveal neoplasia distinctively from normal tissue especially with video software fluorescence analysis. Colorectal tumours of patients were imaged mucosally following ICG administration (0.25 mg/kg i.v.) using an endo-laparoscopic NIR system (PINPOINT Endoscopic Fluorescence System, Stryker) including immediate, continuous in situ visualization of rectal lesions transanally for up to 20 min. Spot and dynamic temporal fluorescence intensities (FI) were quantified using ImageJ (including videos at one frame/second, fps) and by a bespoke MATLAB® application that provided digitalized video tracking and signal logging at 30fps (Fluorescence Tracker App downloadable via MATLAB® file exchange). Statistical analysis of FI-time plots compared tumours (benign and malignant) against control during FI curve rise, peak and decline from apex. Early kinetic FI signal measurement delineated discriminative temporal signatures from tumours (n = 20, 9 cancers) offering rich data for analysis versus delayed spot measurement (n = 10 cancers). Malignant lesion dynamic curves peaked significantly later with a shallower gradient than normal tissue while benign lesions showed significantly greater and faster intensity drop from apex versus cancer. Automated tracker quantification efficiently expanded manual results and provided algorithmic KNN clustering. Photobleaching appeared clinically irrelevant. Analysis of a continuous stream of intraoperatively acquired early ICG fluorescence data can act as an in situ tumour-identifier with greater detail than later snapshot observation alone. Software quantification of such kinetic signatures may distinguish invasive from non-invasive neoplasia with potential for real-time in silico diagnosis.

A Real-Time Video Tracking System

1979 ◽  
Vol 18 (1) ◽  
pp. 180125
Author(s):  
A. L. Gilbert
Keyword(s):  
Real Time ◽  
Tracking System ◽  
Video Tracking ◽  
Video Tracking System

A Holistic Cloud-Enabled Robotics System for Real-Time Video Tracking Application

2014 ◽  
pp. 455-468 ◽  
Author(s):  
Bingwei Liu ◽  
Yu Chen ◽  
Erik Blasch ◽  
Khanh Pham ◽  
Dan Shen ◽  
...  
Keyword(s):  
Real Time ◽  
Video Tracking

Real-Time Tabu Search for Video Tracking Association

2009 ◽  
pp. 21-34 ◽  
Author(s):  
Ivan Dotu ◽  
Pascal Van Hentenryck ◽  
Miguel A. Patricio ◽  
A. Berlanga ◽  
Jose García ◽  
...  
Keyword(s):  
Tabu Search ◽  
Real Time ◽  
Video Tracking

scholarly journals An improved light dark box test by using a real-time video tracking system

2018 ◽  
Vol 69 (4) ◽  
pp. 371-384
Author(s):  
Sareesh Naduvil Narayanan ◽  
Raju Suresh Kumar
Keyword(s):  
Real Time ◽  
Tracking System ◽  
Video Tracking ◽  
Video Tracking System ◽  
Light Dark Box

A Real-Time Video Tracking System

1980 ◽  
Vol PAMI-2 (1) ◽  
pp. 47-56 ◽  
Author(s):  
Alton L. Gilbert ◽  
Michael K. Giles ◽  
Gerald M. Flachs ◽  
Robert B. Rogers ◽  
U Yee Hsun
Keyword(s):  
Real Time ◽  
Tracking System ◽  
Video Tracking ◽  
Video Tracking System

scholarly journals Integrating real-time data analysis into automatic tracking of social insects

2021 ◽  
Vol 8 (3) ◽  
Author(s):  
Alessio Sclocco ◽  
Shirlyn Jia Yun Ong ◽  
Sai Yan Pyay Aung ◽  
Serafino Teseo
Keyword(s):  
Data Analysis ◽  
Real Time ◽  
Recognition Algorithm ◽  
Video Tracking ◽  
Human Observer ◽  
Data Generation ◽  
Time Data ◽  
Real Time Data ◽  
Low Efficiency ◽  
Matrix Codes

Automatic video tracking has become a standard tool for investigating the social behaviour of insects. The recent integration of computer vision in tracking technologies will probably lead to fully automated behavioural pattern classification within the next few years. However, many current systems rely on offline data analysis and use computationally expensive techniques to track pre-recorded videos. To address this gap, we developed BACH (Behaviour Analysis maCHine), a software that performs video tracking of insect groups in real time. BACH uses object recognition via convolutional neural networks and identifies individually tagged insects via an existing matrix code recognition algorithm. We compared the tracking performances of BACH and a human observer (HO) across a series of short videos of ants moving in a two-dimensional arena. We found that BACH detected ant shapes only slightly worse than the HO. However, its matrix code-mediated identification of individual ants only attained human-comparable levels when ants moved relatively slowly, and fell when ants walked relatively fast. This happened because BACH had a relatively low efficiency in detecting matrix codes in blurry images of ants walking at high speeds. BACH needs to undergo hardware and software adjustments to overcome its present limits. Nevertheless, our study emphasizes the possibility of, and the need for, further integrating real-time data analysis into the study of animal behaviour. This will accelerate data generation, visualization and sharing, opening possibilities for conducting fully remote collaborative experiments.

A Fast Search Coil Sensing Method for Tracking Systems

2005 ◽  
Vol 295-296 ◽  
pp. 601-606
Author(s):  
Z.J. Cai ◽  
Li Jiang Zeng
Keyword(s):  
Real Time ◽  
Video Tracking ◽  
Flight Performance ◽  
Tracking Systems ◽  
Feedback Information ◽  
Magnetic Device ◽  
Fast Search ◽  
Search Coil

It is important to track a free flying insect to investigate its flight performance. Conventional video tracking systems are difficult to track a highly maneuverable insect, because the capture frequency of the camera is limited and it can hardly get the position of the insect in real time. We proposed a fast sensing method for insect tracking based on magnetic search coil sensors. It can simultaneously determine the orientation and position of the sensors. We constructed a system, calibrated the magnetic device. We developed a set of calculating methods and measured several positions and angles of coil sensors. The results show that it can rapidly provide the tracking feedback information to meet the requirement for insect tracking.

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