scholarly journals Dual CNN-based Face Tracking Algorithm for an Automated Infant Monitoring System

2021 ◽  
Author(s):  
Cheng Li ◽  
Genyu Song ◽  
A. Pourtaherian ◽  
P. N. de With
Keyword(s):  
Monitoring System ◽  
Face Tracking ◽  
Tracking Algorithm

Robust face tracking algorithm with occlusions

2007 ◽  
Author(s):  
Zhanqing Wang ◽  
Youfu Fan ◽  
Guilin Zhang ◽  
Ruolan Hu
Keyword(s):  
Face Tracking ◽  
Tracking Algorithm

scholarly journals Research on Multi-feature Adaptive Fusion Face Tracking Algorithm

2020 ◽  
Vol 1518 ◽  
pp. 012021
Author(s):  
Qing Lei ◽  
Zhijun Li ◽  
Motao Wang ◽  
Jun Feng ◽  
Rui Zhang
Keyword(s):  
Face Tracking ◽  
Tracking Algorithm ◽  
Adaptive Fusion

scholarly journals A Face Tracking Algorithm for User Interaction in Mobile Devices

2009 ◽  
Author(s):  
Abdullah Bulbul ◽  
Zeynep Cipiloglu ◽  
Tolga Capin
Keyword(s):  
Mobile Devices ◽  
User Interaction ◽  
Face Tracking ◽  
Tracking Algorithm

scholarly journals Application of Optical Flow Technique and Photogrammetry for Rockfall Dynamics: A Case Study on a Field Test

2021 ◽  
Vol 13 (20) ◽  
pp. 4124
Author(s):  
Dong-Hyun Kim ◽  
Ivan Gratchev
Keyword(s):  
Optical Flow ◽  
Dynamic Behavior ◽  
Monitoring System ◽  
Field Test ◽  
Current Approach ◽  
Tracking Algorithm ◽  
Motion Data ◽  
Slope Monitoring

Optical flow is a vision-based approach that is used for tracking the movement of objects. This robust technique can be an effective tool for determining the source of failures on slope surfaces, including the dynamic behavior of rockfall. However, optical flow-based measurement still remains an issue as the data from optical flow algorithms can be affected by the varied photographing environment, such as weather and illuminations. To address such problems, this paper presents an optical flow-based tracking algorithm that can be employed to extract motion data from video records for slope monitoring. Additionally, a workflow combined with photogrammetry and the optical flow technique has been proposed for producing highly accurate estimations of rockfall motion. The effectiveness of the proposed approach has been evaluated with the dataset obtained from a photogrammetry survey of field rockfall tests performed by the authors in 2015. The results show that the workflow adopted in this study can be suitable to identify rockfall events overtime in a slope monitoring system. The limitations of the current approach are also discussed.

scholarly journals Non-Contact Measurement of the Surface Displacement of a Slope Based on a Smart Binocular Vision System

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 2890 ◽  
Author(s):  
Leping He ◽  
Jie Tan ◽  
Qijun Hu ◽  
Songsheng He ◽  
Qijie Cai ◽  
...  
Keyword(s):  
Monitoring System ◽  
Template Matching ◽  
High Speed ◽  
Surface Deformation ◽  
Least Squares Method ◽  
Vision System ◽  
Deformation Monitoring ◽  
Tracking Algorithm ◽  
Zernike Moment ◽  
Tracking Accuracy

The paper presents an intelligent real-time slope surface deformation monitoring system based on binocular stereo-vision. To adapt the system to field slope monitoring, a design scheme of concentric marking point is proposed. Techniques including Zernike moment edge extraction, the least squares method, and k-means clustering are used to design a sub-pixel precision localization method for marker images. This study is mostly focused on the tracking accuracy of objects in multi-frame images obtained from a binocular camera. For this purpose, the Upsampled Cross Correlation (UCC) sub-pixel template matching technique is employed to improve the spatial-temporal contextual (STC) target-tracking algorithm. As a result, the tracking accuracy is improved to the sub-pixel level while keeping the STC tracking algorithm at high speed. The performance of the proposed vision monitoring system has been well verified through laboratory tests.

Development of the human face tracking algorithm based on the optical flow application

2018 ◽  
Vol 10 (5) ◽  
pp. 86-101
Author(s):  
A.A. Druki ◽  
V.G. Spitsyn ◽  
Yu.A. Bolotova ◽  
D. Oliva ◽  
A.V. Gelginberg
Keyword(s):  
Optical Flow ◽  
Face Tracking ◽  
Tracking Algorithm ◽  
Human Face

Mini UAV Orientation Control based on Face Tracking Algorithm

2021 ◽  
Author(s):  
Muhammad Dava Renaldi ◽  
Muhamad Rausyan Fikri ◽  
Djati Wibowo Djamari
Keyword(s):  
Face Tracking ◽  
Tracking Algorithm ◽  
Orientation Control
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