Forensic video solution using facial feature‐based synoptic Video Footage Record

2016 ◽  
Vol 10 (4) ◽  
pp. 315-322 ◽  
Author(s):  
Yogameena Balasubramanian ◽  
Kokila Sivasankaran ◽  
Sindhu Priya Krishraj
Keyword(s):  
Facial Feature ◽  
Video Footage ◽  
Feature Based

Automated Region-Based Vehicle Conflict Detection Using Computer Vision Techniques

2015 ◽  
Vol 2528 (1) ◽  
pp. 49-59
Author(s):  
Jinling Li ◽  
Yuhao Liu ◽  
Ahmed Tageldin ◽  
Mohamed H. Zaki ◽  
Greg Mori ◽  
...  
Keyword(s):  
Computer Vision ◽  
Three Dimensional ◽  
Data Set ◽  
Time To Collision ◽  
Video Footage ◽  
Precise Calculation ◽  
Vehicle Trajectories ◽  
Traffic Conflict ◽  
Point Representation ◽  
Feature Based

An approach for vehicle conflict analysis based on three-dimensional (3-D) vehicle detection is presented. Techniques for quantitative conflict measurements often use a point trajectory representation for vehicles. More accurate conflict measurement can be facilitated with a region-based vehicle representation instead. This paper describes a computer vision approach for extracting vehicle trajectories from video sequences. The method relied on a fusion of background subtraction and feature-based tracking to provide a three-dimensional (3-D) cuboid representation of the vehicle. Standard conflict measures, including time to collision and postencroachment time, were computed with the use of the 3-D cuboid vehicle representations. The use of these conflict measures was demonstrated on a challenging data set of video footage. Results showed that the region-based representation could provide more precise calculation of traffic conflict indicators compared with approaches based on a point representation.

scholarly journals Deep-Facial Feature-Based Person Reidentification for Authentication in Surveillance Applications

2019 ◽  
Author(s):  
Yogameena Balasubramanian ◽  
Nagavani Chandrasekaran ◽  
Sangeetha Asokan ◽  
Saravana Sri Subramanian
Keyword(s):  
Facial Feature ◽  
Feature Based ◽  
Surveillance Applications

Automated In-Radius Authenticated Attendance System

2020 ◽  
Vol 17 (8) ◽  
pp. 3349-3354
Author(s):  
K. Ashok Kumar ◽  
Velagala Tarun Kumar Reddy ◽  
Vemula Shanmukha Srinivas
Keyword(s):  
Higher Education ◽  
Computational Intelligence ◽  
International Workshop ◽  
Near Field ◽  
Facial Feature ◽  
Near Field Communication ◽  
Student Attendance ◽  
Smart Classroom ◽  
Classroom Effects ◽  
Feature Based

Attendance is the most time-consuming task though there exist alternatives a specified device is essential to mark attendance some of them are NFC (Mohd Ameer Hakim bin Mohd Nasir and Muhammad Hazimuddin bin Asmuni, 2015. A review of student attendance system using near-field communication (NFC) technology; Ichimura, T. and Kamada, S., 2013. Early Discovery of Chronic Non-Attenders by Using NFC Attendance Management System. IEEE 6th International Workshop on Computational Intelligence and Applications, Hiroshima, IEEE. pp.191–196; FernAndez, M.J.L., et al., 2013. Control of attendance applied in higher education through mobile NFC technologies. Expert Systems with Applications, 40(1), pp.4478–4489; Shen C.W., et al., 2014. Developing a NFC-equipped smart classroom: Effects on attitudes toward computer science. Computers in Human Behavior, 30, pp.731–738.) based attendance, facial feature-based attendance, RFID based attendance, biometric based attendance. Each attendance system mentioned above have its own disadvantages and spamming techniques which makes students to make themselves present though they are not. So, we came up with an idea to overcome all those defects and complete the task within seconds.

scholarly journals Tracking Subtle Stereotypes of Children with Trisomy 21: From Facial-Feature-Based to Implicit Stereotyping

PLoS ONE ◽  
2012 ◽  
Vol 7 (4) ◽  
pp. e34369 ◽  
Author(s):  
Claire Enea-Drapeau ◽  
Michèle Carlier ◽  
Pascal Huguet
Keyword(s):  
Trisomy 21 ◽  
Facial Feature ◽  
Feature Based ◽  
Implicit Stereotyping
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