1) Background/ Problem Statement
Detecting human beings accurately is very crucial for diverse application areas including abnormal event detection, congestion analysis, person identification, and gender classification. The object classification methods could be divided into three categories: shape-based, motion-based and texture-based.
Human detection is a difficult task from a machine vision perspective as it is influenced by a wide range of possible appearances due to changing articulated pose, clothing, lighting and background, but prior knowledge of these limitations can improve the detection performance.
This system implements algorithms such as the HOG Descriptor algorithm and Support Vector Machine algorithm.
1) 2 Working of the Project
The front-end involves Html, CSS, and JavaScript and the back-end involves Python. Here, the IDE used is Android Studio. The framework used is Django and the database is MySQL.
Here, we focus on detecting humans and do not consider recognition of their activities.
13) Advantages
· It’s easy to maintain.
· It’s user-friendly.
Humans can be detected from any given image, video or from webcam
14) System Description
The system comprises 1 major module with their sub-modules as follows:
User:
· Detection
- Image
The user has to upload an image for detection
- Video
The user has to upload a video for detection
- Real-time
With a click of the button, the camera will open to detect in real-time
15)Project Life Cycle
The waterfall model is a classical model used in the system development life cycle to create a system with a linear and sequential approach. It is termed a waterfall because the model develops systematically from one phase to another in a downward fashion. The waterfall approach does not define the process to go back to the previous phase to handle changes in requirements. The waterfall approach is the earliest approach that was used for software development.
1) System Requirements
I. Hardware Requirement
i. Laptop or PC
· Windows 7 or higher
· I3 processor system or higher
· 4 GB RAM or higher
· 100 GB ROM or higher
II. Software Requirement
ii. Laptop or PC
· Python
· Sublime text Editor
· XAMP Server
71) Limitation/Disadvantages
- The image or video must be of high quality in order to detect humans.
2) 8Application – This application detects humans and their counting from images, videos and even the webcam
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