Detection and tracking of facial features in real time using a synergistic approach of spatio-temporal models and generalized Hough-transform techniques

2002 ◽  
Author(s):  
A. Schubert
Keyword(s):  
Real Time ◽  
Hough Transform ◽  
Facial Features ◽  
Generalized Hough Transform ◽  
Detection And Tracking ◽  
Temporal Models ◽  
Synergistic Approach ◽  
Spatio Temporal

scholarly journals FACIAL FEATURES DETECTION USING TEXTURE HOUGH TRANSFORM

2015 ◽  
Vol XL-5/W6 ◽  
pp. 107-111 ◽  
Author(s):  
V. S. Gorbatsevich
Keyword(s):  
Object Detection ◽  
Hough Transform ◽  
Main Tool ◽  
Original Method ◽  
Facial Features ◽  
Training Set ◽  
Generalized Hough Transform ◽  
Lbp Descriptor

The paper presents an original method for object detection. The “texture” Hough transform is used as the main tool in the search. Unlike classical generalized Hough transform, this variation uses texture LBP descriptor as a primitive for voting. The voting weight of each primitive is assumed by learning at a training set. This paper gives an overview of an original method for weights learning, and a number of ways to get the maximum searching algorithm speed on practice.

scholarly journals Towards Real-Time Detection and Tracking of Spatio-Temporal Features: Blob-Filaments in Fusion Plasma

2016 ◽  
Vol 2 (3) ◽  
pp. 262-275 ◽  
Author(s):  
Lingfei Wu ◽  
Kesheng John Wu ◽  
Alex Sim ◽  
Michael Churchill ◽  
Jong Y. Choi ◽  
...  
Keyword(s):  
Real Time ◽  
Fusion Plasma ◽  
Detection And Tracking ◽  
Temporal Features ◽  
Real Time Detection ◽  
Spatio Temporal

Windage Yaw Angle Detection of Suspension Insulator Strings Based on Edge Feature Matching

2012 ◽  
Vol 241-244 ◽  
pp. 98-103
Author(s):  
Hai Jun Lu ◽  
Yu Xiang Lv ◽  
Wei Qing Ma ◽  
Xiao Long Zhao ◽  
Xue Lian Zheng
Keyword(s):  
Real Time ◽  
Hough Transform ◽  
Feature Matching ◽  
Matching Accuracy ◽  
A Algorithm ◽  
Generalized Hough Transform ◽  
Suspension Insulator ◽  
Depth Analysis ◽  
Yaw Angle ◽  
Edge Feature

By in-depth analysis and summary of tower suspension insulator strings images collected, a algorithm of edge feature matching of suspension insulator strings was proposed to detect the windage yaw angle in real-time. By filter, image grayscale, interframe difference and edge feature matching which based on invariance Generalized Hough Transform (IGHT) and local feature of suspension insulator strings stored in a database, the coordinates of the ends of suspension insulator strings were determined, and then the size of windage yaw angle of suspension insulator strings was calculated. The algorithm proposed can provide translation, scaling and rotation invariance, and be better matching accuracy and robustness.

scholarly journals Sports Video Augmented Reality Real-Time Image Analysis of Mobile Devices

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Hui Wang ◽  
Meng Wang ◽  
Peng Zhao
Keyword(s):  
Augmented Reality ◽  
Real Time ◽  
Mobile Devices ◽  
Hough Transform ◽  
Feature Matching ◽  
Tracking Algorithm ◽  
Sports Video ◽  
Detection And Tracking ◽  
Real Time Image ◽  
Time Image

Sports video is loved by the audience because of its unique charm, so it has high research value and application value to analyze and study the video data of competition. Based on the background of football match, this paper studies the football detection and tracking algorithm in football game video and analyzes the real-time image of real-time mobile devices in sports video augmented reality. Firstly, the image is preprocessed by image graying, image denoising, image binarization, and so on. Secondly, Hough transform is used to locate and detect football, and according to the characteristics of football, Hough transform is improved. Based on the good performance of SIFT algorithm in feature matching, a football tracking algorithm based on SIFT feature matching is proposed, which matches the detected football with the sample football. The simulation results show that the improved Hough transform can effectively detect football and has good antijamming performance. And the designed football tracking algorithm based on SIFT feature matching can accurately track the football trajectory; therefore, the football detection and tracking algorithm designed in this paper is suitable for real-time football monitoring and tracking.

Real-time pattern recognition using an optical generalized Hough transform

2015 ◽  
Vol 54 (36) ◽  
pp. 10586 ◽  
Author(s):  
Ariel Fernández ◽  
Jorge L. Flores ◽  
Julia R. Alonso ◽  
José A. Ferrari
Keyword(s):  
Pattern Recognition ◽  
Real Time ◽  
Hough Transform ◽  
Time Pattern ◽  
Generalized Hough Transform

Real-time hands, face and facial features detection and tracking: Application to cognitive rehabilitation tests monitoring

2010 ◽  
Vol 33 (4) ◽  
pp. 447-466 ◽  
Author(s):  
D. González-Ortega ◽  
F.J. Díaz-Pernas ◽  
M. Martínez-Zarzuela ◽  
M. Antón-Rodríguez ◽  
J.F. Díez-Higuera ◽  
...  
Keyword(s):  
Real Time ◽  
Cognitive Rehabilitation ◽  
Facial Features ◽  
Detection And Tracking

Real-time object recognition using a modified generalized Hough transform

2003 ◽  
Vol 36 (11) ◽  
pp. 2557-2570 ◽  
Author(s):  
Markus Ulrich ◽  
Carsten Steger ◽  
Albert Baumgartner
Keyword(s):  
Object Recognition ◽  
Real Time ◽  
Hough Transform ◽  
Generalized Hough Transform

scholarly journals Pyramidal Framework: Guidance for the Next Generation of GIS Spatial-Temporal Models

2021 ◽  
Vol 10 (3) ◽  
pp. 188
Author(s):  
Cyril Carré ◽  
Younes Hamdani
Keyword(s):  
Conceptual Models ◽  
Future Generations ◽  
Temporal Data ◽  
Temporal Modeling ◽  
Temporal Models ◽  
Gis Data ◽  
Spatio Temporal ◽  
New Interpretation ◽  
Conventional Literature

Over the last decade, innovative computer technologies and the multiplication of geospatial data acquisition solutions have transformed the geographic information systems (GIS) landscape and opened up new opportunities to close the gap between GIS and the dynamics of geographic phenomena. There is a demand to further develop spatio-temporal conceptual models to comprehensively represent the nature of the evolution of geographic objects. The latter involves a set of considerations like those related to managing changes and object identities, modeling possible causal relations, and integrating multiple interpretations. While conventional literature generally presents these concepts separately and rarely approaches them from a holistic perspective, they are in fact interrelated. Therefore, we believe that the semantics of modeling would be improved by considering these concepts jointly. In this work, we propose to represent these interrelationships in the form of a hierarchical pyramidal framework and to further explore this set of concepts. The objective of this framework is to provide a guideline to orient the design of future generations of GIS data models, enabling them to achieve a better representation of available spatio-temporal data. In addition, this framework aims at providing keys for a new interpretation and classification of spatio-temporal conceptual models. This work can be beneficial for researchers, students, and developers interested in advanced spatio-temporal modeling.

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