scholarly journals Detection and classification of vehicles for traffic video analytics

2018 ◽  
Vol 144 ◽  
pp. 259-268 ◽  
Author(s):  
Ahmad Arinaldi ◽  
Jaka Arya Pradana ◽  
Arlan Arventa Gurusinga
Keyword(s):  
Video Analytics ◽  
Traffic Video

Assessment of the predictive capability of the biometric video analytics complex for improving the professional psychophysiological selection of candidates for military educational institutions

2020 ◽  
pp. 484-488
Author(s):  
P. I. Dmitriev ◽  
S. V. Chermyanin ◽  
I. A. Roznova
Keyword(s):  
Deviant Behavior ◽  
Predictive Ability ◽  
Educational Institutions ◽  
Eye Tracker ◽  
Video Analytics ◽  
Software Complex ◽  
Stage Of Development ◽  
New Instrumentation ◽  
Scientific Substantiation

At the present stage of development of labor physiology, the issues of scientific substantiation of research methods for the professional suitability of candidates for military specialties and their new instrumentation remain relevant in connection with the increasing requirements of the profession to the psychophysiological capabilities and qualities of employees.The aim of study is to assess the predictive ability of the biometric video analytics system (for example, the “MIX-GT–19” complex) to determine the professional fitness of military personnel.The method of videoculographic recording of responses was used to examine young men aged 17–20 years, classified in different categories of professional aptitude, when answering questions from two types of express questionnaires (adaptation and deviant behavior).A classification of modern systems of biometric video analytics is proposed. The principles of their operation and functionality are described. The prognostic ability of the MIX-GT–19 complex was evaluated by identifying the correlation of its operation with the MLO “Adaptability” method of operation. The results of research conducted using the “MIX-GT–19” complex are presented. The prospects for its further development and application are described.The physiological efficiency of using hardware and software complex (HSC) based on eye-tracker technology for the purposes of professional selection by studying psychophysiological and behavioral responses is established.

Shape Features of Overlapping Boundary for Classification of Moving Vehicles

2013 ◽  
Vol 3 (1) ◽  
pp. 42-54
Author(s):  
Elham Dallalzadeh ◽  
D. S. Guru
Keyword(s):  
Video Sequences ◽  
Shape Features ◽  
Tracking Method ◽  
Boundary Shape ◽  
Moving Vehicles ◽  
Different Types ◽  
Traffic Video ◽  
Boundary Curves

In this paper, the authors propose a model for classification of moving vehicles in traffic videos. A corner-based tracking method is presented to track and detect moving vehicles. The authors propose to overlap the boundary curves of each of the detected moving vehicles while tracking in a sequence of frames to reconstruct a complete boundary shape of the vehicle. The reconstructed boundary shape is normalized and then shape features are extracted. Vehicles are categorized into 4 different types of vehicle classes using KNN rule, the weighted KNN, PNN, and SVM classifiers. Experiments are conducted on traffic video sequences captured in an uncontrolled environment during daytime.

scholarly journals Simplified Video Surveillance Framework for Dynamic Object Detection under Challenging Environment

2019 ◽  
Vol 9 (4) ◽  
pp. 2715
Author(s):  
Madhu Chandra G. ◽  
Sreerama Reddy G. M
Keyword(s):  
Video Surveillance ◽  
Research Trends ◽  
Depth Image ◽  
Illumination Condition ◽  
Video Analytics ◽  
Significant Information ◽  
Video File ◽  
Challenging Environment ◽  
Video Feed

An effective video surveillance system is highly essential in order to ensure constructing better form of video analytics. Existing review of literatures pertaining to video analytics are found to directly implement algorithms on the top of the video file without much emphasis on following problems i.e. i) dynamic orientation of subject, ii)poor illumination condition, iii) identification and classification of subjects, and iv) faster response time. Therefore, the proposed system implements an analytical concept that uses depth-image of the video feed along with the original colored video feed to apply an algorithm for extracting significant information about the motion blob of the dynamic subjects. Implemented in MATLAB, the study outcome shows that it is capable of addressing all the above mentioned problems associated with existing research trends on video analytics by using a very simple and non-iterative process of implementation. The applicability of the proposed system in practical world is thereby proven.

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