human age/gender detection module
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Human Age/Gender Detection ModuleProject: Automatic Surveillance System for Video Streams (ASSVS)
November 24, 2016
Contents
1
Chapter 1
Introduction
1.1 Purpose
This document provides the requirement specifications for age and gender detection module. Itcovers module requirements, assumptions and dependencies, constraints, mock-up user interface,and operating environment for the module.
1.2 Module Scope
The scope of age and gender detection module is described in this section:
1.2.1 Age Detection
The age is detected using the following categorization:
• Baby (0-2 years)
• Adult (20-50 years)
• Old (60+ years)
1.2.2 Gender Detection
Detected gender for adult and old will be:
• Male
• Female
2
Chapter 2
Overall Description
2.1 Module Perspective
Age and gender detection module is part of the ASSVS project which will enable quick identifica-tion of age and gender of the persons present in the videos. The module will get input from Facedetection module in the form of facial region. After age and gender detection, the module will beproviding the keyword output to natural language generation module for further processing. Abrief overview of interfacing between the module and rest of the framework is shown in figure ??.
Figure 2.1: Age and gender detection module in ASSVS framework
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CHAPTER 2. OVERALL DESCRIPTION 4
2.2 Module Functions
Functions Description
Age Detection Human age is detected for different classes: baby, adult or old.
Gender Detection Human gender is detected for different classes: male or female.
2.3 User Classes and Characteristics
• Law enforcement officials
• Bank marketing managers
2.4 Design and Implementation Constraints
• The module will only work for frontal face cropped images.
• Age classes instead of exact age will be detected as mentioned in scope.
• Occlusions or truncation will make it hard to detect age and gender. Occlusions may include:
– Male: beard, glasses etc.
– Females: veils, scarf, heavy makeup etc.
2.5 Assumptions and Dependencies
• Frontal face cropped regions are provided to the module.
• The module has a dependency on face detection module.
2.6 User Documentation
User manual will be provided with the software that will help end users in installation and usageof the software.
Chapter 3
External Interface Requirements
3.1 User Interfaces
User will be able to provide input from camera or recorded video. The video will be displayed inthe middle panel. Detected age and gender will appear in the left panel. Right panel will showthe cropped faces with annotations of age and gender. The summary of detected age and genderbased on filters shall be displayed below. A mock-up user interface is shown in figure ??.
Figure 3.1: User interface for age and gender detection module
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CHAPTER 3. EXTERNAL INTERFACE REQUIREMENTS 6
3.2 Software Interfaces
Operating System Windows
.NET Framework v4.0
IDE Visual Studio 2013
Database MS SQL SERVER 2008
Image Processing Libraries OpenCV 3.0, EmguCV 3.0
Machine Learning API Accord.NET
Database IDE SQL Server Management Studio
Web Server IIS 8
3.3 Hardware Interface
Processor Quad-Core 3.4 GHz
RAM DDR3 16GB RAM
Camera FHD
DVR Any
Storage Device 1TB
Network Bandwidth 1MBps
Graphics Card Nvidia
3.4 Operating Environment
As this module is a part of surveillance system, monitoring the behavior of humans. This caninclude observing a subject from a distance using electronic devices like CCTV cameras. Systemcan work in indoor environment as well as outdoor environment with the concerns that minimumlighting conditions are satisfied. This module is an independent system that can act as an inputof different applications and can also act as a subsystem for a surveillance system.
Chapter 4
System Features
4.1 Product Perspective
Use case diagram of this system is presented in figure ??.
Gender Detection
Age Detection
Face detection
Figure 4.1: Product Perspective
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CHAPTER 4. SYSTEM FEATURES 8
4.2 Age Detection
4.2.1 Description and Priority
Age detection will enable user to classify people in different age groups. It has same priority asthat of gender detection.
4.2.2 Stimulus/Response Sequences
Stimulus: The user provides camera or recorded video as input and requests for age detection.Response: The system returns detected age and its summary in video.
4.2.3 Functional Requirements
FR-1: Cropped frontal face image from video will be used to detect human age.
4.3 Gender Detection
4.3.1 Description and Priority
Gender detection identifies humans gender from video stream. It has same priority as that of Agedetection in this module.
4.3.2 Stimulus/Response Sequences
Stimulus: The user provides camera or recorded video as input and requests for gender detection.Response: The system returns detected gender information and its summary in provided video.
4.3.3 Functional Requirements
FR-1: Cropped frontal face image from video will be used to detect human gender.
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