The Solution to Background Segmentation and Extraction in Traffic Video Detection

2012 ◽  
Author(s):  
Zewei Xu ◽  
Qizhi Qiu ◽  
Lu Wang
Keyword(s):  
Video Detection ◽  
Background Segmentation ◽  
Traffic Video

scholarly journals Occlusion Processing and Tracking Technology of Multiple Targets in Traffic Video Detection

2014 ◽  
Vol 7 (1) ◽  
pp. 326395
Author(s):  
Yingying Zhao ◽  
Sheng Jiang ◽  
Zhaowei Qu ◽  
Pengfei Tao
Keyword(s):  
Multiple Targets ◽  
Video Detection ◽  
Traffic Video ◽  
Tracking Technology

scholarly journals Ground Truth Generating Tool for Traffic Video Detector

2015 ◽  
Vol 20 (2) ◽  
pp. 17-27
Author(s):  
Szymon Bigaj ◽  
Andrzej Głowacz ◽  
Jacek Kościow ◽  
Zbigniew Mikrut ◽  
Piotr Pawlik
Keyword(s):  
Comparative Analysis ◽  
Road Traffic ◽  
Ground Truth ◽  
Detection Algorithm ◽  
Ground Truth Data ◽  
Video Detection ◽  
Detection Software ◽  
Traffic Video ◽  
Video Detector

Abstract The paper presents an application for generating ground truth data for the purposes of video detection and justifies its use in systems which analyze road traffic videos. The usefulness of described application in the development of video detection software is presented - especially during scene configuration and comparative analysis of video detection results versus ground truth data. The latter is possible due to simplicity of the result text files generated in a similar way both by the presented application and by the video detection algorithm. Two exemplary applications of the tool designed to generate ground truth data are presented, together with a discussion of their construction, functionality and abilities.

Segmentation In Medical Resonance images to extract the cancerous nodule for early diagnosis on cancer

2012 ◽  
Vol 3 (2) ◽  
pp. 253-255
Author(s):  
Raman Brar
Keyword(s):  
Human Lung ◽  
Research Work ◽  
Vital Role ◽  
Watershed Algorithm ◽  
Segmentation Method ◽  
Resonance Imaging ◽  
Segmentation Methods ◽  
Segmentation Accuracy ◽  
Background Segmentation ◽  
Lung Mri

Image segmentation plays a vital role in several medical imaging programs by assisting the delineation of physiological structures along with other parts. The objective of this research work is to segmentize human lung MRI (Medical resonance Imaging) images for early detection of cancer.Watershed Transform Technique is implemented as the Segmentation method in this work. Some comparative experiments using both directly applied watershed algorithm and after marking foreground and computed background segmentation methods show the improved lung segmentation accuracy in some image cases.

Deepfake Video Detection Based on Spatial, Spectral, and Temporal Inconsistencies Using Multimodal Deep Learning

2020 ◽  
Author(s):  
John K. Lewis ◽  
Imad Eddine Toubal ◽  
Helen Chen ◽  
Vishal Sandesera ◽  
Michael Lomnitz ◽  
...  
Keyword(s):  
Deep Learning ◽  
Video Detection

scholarly journals Audio-Video detection of the active speaker in meetings

2021 ◽  
Author(s):  
Francisco Madrigal ◽  
Frederic Lerasle ◽  
Lionel Pibre ◽  
Isabelle Ferrane
Keyword(s):  
Video Detection ◽  
Audio Video
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