Three-View Surveillance Video Based Face Modeling for Recogniton

2007 ◽  
Author(s):  
Scott von Duhn ◽  
Myung Jin Ko ◽  
Lijun Yin ◽  
Terry Hung ◽  
Xiaozhou Wei
Keyword(s):  
Surveillance Video ◽  
Face Modeling

Multiprocessor transport surveillance video system based on "system on chip" technology

2020 ◽  
Author(s):  
Ш.С. Фахми ◽  
Н.В. Шаталова ◽  
В.В. Вислогузов ◽  
Е.В. Костикова
Keyword(s):  
System On Chip ◽  
Reference Points ◽  
Surveillance Video ◽  
Video Information ◽  
Chip Technology ◽  
Intelligent Video Surveillance System ◽  
Speed Up ◽  
Algorithmic Analysis ◽  
Computational Procedures ◽  
On Chip

В данной работе предлагаются математический аппарат и архитектура многопроцессорной транспортной системы на кристалле (МПТСнК). Выполнена программно-аппаратная реализация интеллектуальной системы видеонаблюдения на базе технологии «система на кристалле» и с использованием аппаратного ускорителя известного метода формирования опорных векторов. Архитектура включает в себя сложно-функциональные блоки анализа видеоинформации на базе параллельных алгоритмов нахождения опорных точек изображений и множества элементарных процессоров для выполнения сложных вычислительных процедур алгоритмов анализа с использованием средств проектирования на базе реконфигурируемой системы на кристалле, позволяющей оценить количество аппаратных ресурсов. Предлагаемая архитектура МПТСнК позволяет ускорить обработку и анализ видеоинформации при решении задач обнаружения и распознавания чрезвычайных ситуаций и подозрительных поведений. In this paper, we propose the mathematical apparatus and architecture of a multiprocessor transport system on a chip (MPTSoC). Software and hardware implementation of an intelligent video surveillance system based on the "system on chip" technology and using a hardware accelerator of the well-known method of forming reference vectors. The architecture includes complex functional blocks for analyzing video information based on parallel algorithms for finding image reference points and a set of elementary processors for performing complex computational procedures for algorithmic analysis. using design tools based on a reconfigurable system on chip that allows you to estimate the amount of hardware resources. The proposed MPTSoC architecture makes it possible to speed up the processing and analysis of video information when solving problems of detecting and recognizing emergencies and suspicious behaviors

scholarly journals Intelligent vehicle modeling design based on image processing

2021 ◽  
Vol 18 (1) ◽  
pp. 172988142199334
Author(s):  
Guangchao Zhang ◽  
Junrong Liu
Keyword(s):  
Image Data ◽  
Front Face ◽  
Intelligent Vehicle ◽  
Surface Model ◽  
Data Sets ◽  
Face Modeling ◽  
Shape Coefficient ◽  
Automotive Market ◽  
Modeling Analysis ◽  
Family Analysis

With the urgent demand of consumers for diversified automobile modeling, simple, efficient, and intelligent automobile modeling analysis and modeling method is an urgent problem to be solved in current automobile modeling design. The purpose of this article is to analyze the modeling preference and trend of the current automobile market in time, which can assist the modeling design of new models of automobile main engine factories and strengthen their branding family. Intelligent rapid modeling shortens the current modeling design cycle, so that the product rapid iteration is to occupy an active position in the automotive market. In this article, aiming at the family analysis of automobile front face, the image database of automobile front face modeling analysis was created. The database included two data sets of vehicle signs and no vehicle signs, and the image data of vehicle front face modeling of most models of 22 domestic mainstream brands were collected. Then, this article adopts the image classification processing method in computer vision to conduct car brand classification training on the database. Based on ResNet-8 and other model architectures, it trains and classifies the intelligent vehicle brand classification database with and without vehicle label. Finally, based on the shape coefficient, a 3D wireframe model and a curved surface model are obtained. The experimental results show that the 3D curve model can be obtained based on a single image from any angle, which greatly shortens the modeling period by 92%.

Two-stream deep spatial-temporal auto-encoder for surveillance video abnormal event detection

2021 ◽  
Vol 439 ◽  
pp. 256-270
Author(s):  
Tong Li ◽  
Xinyue Chen ◽  
Fushun Zhu ◽  
Zhengyu Zhang ◽  
Hua Yan
Keyword(s):  
Event Detection ◽  
Surveillance Video ◽  
Abnormal Event Detection

A Case Study Demonstrating the Utility of Surveillance Video in Assessing Gait Dynamics and Behavior During a Slip and Fall

2020 ◽  
Vol 64 (1) ◽  
pp. 550-554
Author(s):  
Leah S. Hartman ◽  
Stephanie A. Whetsel Borzendowski ◽  
Alan O. Campbell
Keyword(s):  
Human Factors ◽  
Gait Pattern ◽  
Personal Injury ◽  
Objective Data ◽  
Surveillance Video ◽  
Gait Dynamics ◽  
Fall Incident ◽  
The Individual ◽  
And Behavior

As the use of surveillance video at commercial properties becomes more prevalent, it is more likely an incident involving a personal injury will be captured on film. This provides a unique opportunity for Human Factors practitioners involved in forensic investigations to analyze the behavior of the individual prior to, during, and after the event in question. It also provides an opportunity to gather unique and objective data. The present work describes a case study of a slip and fall where surveillance video and onsite measurements were combined and analyzed to quantify a plaintiff’s gait pattern. Using this type of analysis, we were able to determine that the plaintiff was likely aware that the floor was slippery and adjusted her gait and behavior prior to the slip and fall incident.

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