Towards a Semantic Video Analysis using Deep Learning and Ontology

2018 ◽  
Author(s):  
Jemai Bornia ◽  
Sidi Ahmed Mahmoudi ◽  
Ali Frihida ◽  
Pierre Manneback
Keyword(s):  
Deep Learning ◽  
Video Analysis

A unified framework for automated person re-indentification

2020 ◽  
Vol 71 (7) ◽  
pp. 868-880
Author(s):  
Nguyen Hong-Quan ◽  
Nguyen Thuy-Binh ◽  
Tran Duc-Long ◽  
Le Thi-Lan
Keyword(s):  
Deep Learning ◽  
Video Analysis ◽  
Camera Network ◽  
Unified Framework ◽  
Person Detection ◽  
Practical Applications ◽  
Detection And Tracking ◽  
Analysis System ◽  
Bounding Boxes

Along with the strong development of camera networks, a video analysis system has been become more and more popular and has been applied in various practical applications. In this paper, we focus on person re-identification (person ReID) task that is a crucial step of video analysis systems. The purpose of person ReID is to associate multiple images of a given person when moving in a non-overlapping camera network. Many efforts have been made to person ReID. However, most of studies on person ReID only deal with well-alignment bounding boxes which are detected manually and considered as the perfect inputs for person ReID. In fact, when building a fully automated person ReID system the quality of the two previous steps that are person detection and tracking may have a strong effect on the person ReID performance. The contribution of this paper are two-folds. First, a unified framework for person ReID based on deep learning models is proposed. In this framework, the coupling of a deep neural network for person detection and a deep-learning-based tracking method is used. Besides, features extracted from an improved ResNet architecture are proposed for person representation to achieve a higher ReID accuracy. Second, our self-built dataset is introduced and employed for evaluation of all three steps in the fully automated person ReID framework.

Real-time Worker Safety Management System Using Deep Learning-based Video Analysis Algorithm

2020 ◽  
Vol 9 (3) ◽  
pp. 25-30
Author(s):  
So Yeon Jeon ◽  
Jong Hwa Park ◽  
Sang Byung Youn ◽  
Young Soo Kim ◽  
Yong Sung Lee ◽  
...  
Keyword(s):  
Deep Learning ◽  
Real Time ◽  
Video Analysis ◽  
Management System ◽  
Safety Management ◽  
Worker Safety ◽  
Safety Management System ◽  
Analysis Algorithm

Deep learning based basketball video analysis for intelligent arena application

2017 ◽  
Vol 76 (23) ◽  
pp. 24983-25001 ◽  
Author(s):  
Wu Liu ◽  
Chenggang Clarence Yan ◽  
Jiangyu Liu ◽  
Huadong Ma
Keyword(s):  
Deep Learning ◽  
Video Analysis

Deep learning for diplomatic video analysis

2018 ◽  
Vol 79 (7-8) ◽  
pp. 4811-4830
Author(s):  
Hongyan Zhao ◽  
Fangxin Zhou ◽  
Huaping Liu
Keyword(s):  
Deep Learning ◽  
Video Analysis

scholarly journals Deep learning in sport video analysis: a review

2020 ◽  
Vol 18 (4) ◽  
pp. 1926
Author(s):  
Keerthana Rangasamy ◽  
Muhammad Amir As’ari ◽  
Nur Azmina Rahmad ◽  
Nurul Fathiah Ghazali ◽  
Saharudin Ismail
Keyword(s):  
Deep Learning ◽  
Video Analysis ◽  
Sport Video ◽  
Sport Video Analysis

Semantic Map Annotation Through UAV Video Analysis Using Deep Learning Models in ROS

2018 ◽  
pp. 328-340 ◽  
Author(s):  
Efstratios Kakaletsis ◽  
Maria Tzelepi ◽  
Pantelis I. Kaplanoglou ◽  
Charalampos Symeonidis ◽  
Nikos Nikolaidis ◽  
...  
Keyword(s):  
Deep Learning ◽  
Video Analysis ◽  
Learning Models ◽  
Semantic Map
Sign in / Sign up

Export Citation Format

Share Document