Facial feature point location and tracking method based on improved Viola-Jones algorithm and Kalman filter prediction mechanism

2015 ◽  
pp. 873-876
Keyword(s):  
Kalman Filter ◽  
Facial Feature ◽  
Feature Point ◽  
Point Location ◽  
Tracking Method ◽  
Prediction Mechanism

Road rage detection algorithm based on fatigue driving and facial feature point location

2022 ◽  
Author(s):  
Wu Shulei ◽  
Suo Zihang ◽  
Chen Huandong ◽  
Zhao Yuchen ◽  
Zhang Yang ◽  
...  
Keyword(s):  
Facial Feature ◽  
Detection Algorithm ◽  
Feature Point ◽  
Road Rage ◽  
Point Location ◽  
Fatigue Driving

scholarly journals Automatic measurement of traditional Chinese costume from its silhouette through Fuzzy c-means clustering method

2020 ◽  
Vol 15 ◽  
pp. 155892502097832
Author(s):  
Jiaqin Zhang ◽  
Jingan Wang ◽  
Le Xing ◽  
Hui’e Liang
Keyword(s):  
Industrial Application ◽  
Clustering Algorithm ◽  
Color Space ◽  
Automatic Measurement ◽  
Feature Point ◽  
Feature Points ◽  
Point Location ◽  
Fuzzy C Means ◽  
Fuzzy C Means Clustering ◽  
Environmental Robustness

As the precious cultural heritage of the Chinese nation, traditional costumes are in urgent need of scientific research and protection. In particular, there are scanty studies on costume silhouettes, due to the reasons of the need for cultural relic protection, and the strong subjectivity of manual measurement, which limit the accuracy of quantitative research. This paper presents an automatic measurement method for traditional Chinese costume dimensions based on fuzzy C-means clustering and silhouette feature point location. The method is consisted of six steps: (1) costume image acquisition; (2) costume image preprocessing; (3) color space transformation; (4) object clustering segmentation; (5) costume silhouette feature point location; and (6) costume measurement. First, the relative total variation model was used to obtain the environmental robustness and costume color adaptability. Second, the FCM clustering algorithm was used to implement image segmentation to extract the outer silhouette of the costume. Finally, automatic measurement of costume silhouette was achieved by locating its feature points. The experimental results demonstrated that the proposed method could effectively segment the outer silhouette of a costume image and locate the feature points of the silhouette. The measurement accuracy could meet the requirements of industrial application, thus providing the dual value of costume culture research and industrial application.

Multi-Magnet Tracking Method using Extended Kalman Filter*

2021 ◽  
Author(s):  
Han Ge ◽  
Shuang Song ◽  
Jiaole Wang ◽  
Max Q.-H. Meng
Keyword(s):  
Kalman Filter ◽  
Extended Kalman Filter ◽  
Tracking Method

Carrier Tracking Performance Comparison of Standards and the Square-Root Kalman Filter

2012 ◽  
Vol 239-240 ◽  
pp. 1188-1193
Author(s):  
Shao Jie Ni ◽  
Jing Pang ◽  
Xiao Mei Tang ◽  
Fei Xue Wang
Keyword(s):  
Kalman Filter ◽  
Engineering Design ◽  
Performance Comparison ◽  
Tracking Performance ◽  
Square Root ◽  
Signal Tracking ◽  
Tracking Method ◽  
High Carrier ◽  
Comparison Of Standards ◽  
Lock In

In order to solve the problem of loosing lock in weak GPS signal tracking, Kalman filter based carrier tracking method is presented.In this paper,two methods to track the GNSS carrier are compared,one is base on normal Kalman filter, another is based on square-root Kalman filter. The paper analyzes the under performance in the low carrier-to-noise ratio, and the expenditure of the actual project exists, but the high carrier to noise less discussed than the case will appear.The analyse and simulation result can be used to guide the engineering design of the GNSS receiver.

A Robust Facial Feature Tracking Method Based on Optical Flow and Prior Measurement

2010 ◽  
Vol 4 (4) ◽  
pp. 62-75
Author(s):  
Guoyin Wang ◽  
Yong Yang ◽  
Kun He
Keyword(s):  
Optical Flow ◽  
Feature Tracking ◽  
Facial Feature ◽  
Recognition System ◽  
Research Area ◽  
Expression Recognition ◽  
Tracking Method ◽  
Facial Feature Tracking ◽  
Recognition Result ◽  
Method Of Measurement

Cognitive informatics (CI) is a research area including some interdisciplinary topics. Visual tracking is not only an important topic in CI, but also a hot topic in computer vision and facial expression recognition. In this paper, a novel and robust facial feature tracking method is proposed, in which Kanade-Lucas-Tomasi (KLT) optical flow is taken as basis. The prior method of measurement consisting of pupils detecting features restriction and errors and is used to improve the predictions. Simulation experiment results show that the proposed method is superior to the traditional optical flow tracking. Furthermore, the proposed method is used in a real time emotion recognition system and good recognition result is achieved.

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