Real-time detection and tracking for moving objects based on computer vision method

2017 ◽  
Author(s):  
Yi-You Hou ◽  
Sz-Yu Chiou ◽  
Ming-Hung Lin
Keyword(s):  
Computer Vision ◽  
Real Time ◽  
Moving Objects ◽  
Detection And Tracking ◽  
Real Time Detection

scholarly journals DETECTION AND TRACKING OF MOVING OBJECTS WITH REAL-TIME ONBOARD VISION SYSTEM

2017 ◽  
Vol XLII-2/W4 ◽  
pp. 67-71 ◽  
Author(s):  
D. Y. Erokhin ◽  
A. B. Feldman ◽  
S. E. Korepanov
Keyword(s):  
Computer Vision ◽  
Real Time ◽  
Video Sequence ◽  
Moving Objects ◽  
Vision System ◽  
Unmanned Aircraft ◽  
Computer Vision System ◽  
Geometric Transformations ◽  
Detection And Tracking ◽  
Video Sensor

Detection of moving objects in video sequence received from moving video sensor is a one of the most important problem in computer vision. The main purpose of this work is developing set of algorithms, which can detect and track moving objects in real time computer vision system. This set includes three main parts: the algorithm for estimation and compensation of geometric transformations of images, an algorithm for detection of moving objects, an algorithm to tracking of the detected objects and prediction their position. The results can be claimed to create onboard vision systems of aircraft, including those relating to small and unmanned aircraft.

Real time detection and tracking of Gauzes by RFID UWB technique

2010 ◽  
Author(s):  
S. Boncinelli ◽  
P. Citti ◽  
E. Del Re ◽  
G. Campatelli ◽  
L. Pierucci ◽  
...  
Keyword(s):  
Real Time ◽  
Detection And Tracking ◽  
Real Time Detection

Multi Object Detection and Tracking from Video File

2014 ◽  
Vol 533 ◽  
pp. 218-225 ◽  
Author(s):  
Rapee Krerngkamjornkit ◽  
Milan Simic
Keyword(s):  
Computer Vision ◽  
Background Subtraction ◽  
Moving Objects ◽  
Gaussian Mixture Models ◽  
Gaussian Mixture ◽  
Video Tracking ◽  
Partial Occlusion ◽  
Video File ◽  
Detection And Tracking ◽  
Over Time

This paper describes computer vision algorithms for detection, identification, and tracking of moving objects in a video file. The problem of multiple object tracking can be divided into two parts; detecting moving objects in each frame and associating the detections corresponding to the same object over time. The detection of moving objects uses a background subtraction algorithm based on Gaussian mixture models. The motion of each track is estimated by a Kalman filter. The video tracking algorithm was successfully tested using the BIWI walking pedestrians datasets [. The experimental results show that system can operate in real time and successfully detect, track and identify multiple targets in the presence of partial occlusion.

scholarly journals Real Time Detection and Tracking of Spatial Event Clusters

2015 ◽  
pp. 316-319 ◽  
Author(s):  
Natalia Andrienko ◽  
Gennady Andrienko ◽  
Georg Fuchs ◽  
Salvatore Rinzivillo ◽  
Hans-Dieter Betz
Keyword(s):  
Real Time ◽  
Detection And Tracking ◽  
Real Time Detection
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