Computer vision based Human Fall Detection system
In this project, we will develop a novel person specific fall detection system based on a monocular camera, which can be applied for assisting the independent living of an older adult living alone at home. A single camera covering the living area is used for video recordings of an e
2025-06-28 16:30:53 - Adil Khan
Computer vision based Human Fall Detection system
Project Area of Specialization Artificial IntelligenceProject SummaryIn this project, we will develop a novel person specific fall detection system based on a monocular camera,
which can be applied for assisting the independent living of an older adult living alone at home. A single
camera covering the living area is used for video recordings of an
elderly person's normal daily activities.
From the recorded video data, the human silhouette regions in every frame
are then extracted based on
the codebook background subtraction technique. Low-dimensionality
representative features of extracted
silhouetted are then extracted by convolutional neural network based
autoencoder (CNN-AE). Features
obtained from the CNN-AE are applied to construct an one class support
vector machine (OCSVM)
model, which is a data driven model based on the video recordings and can
be applied for fall detection.
From the comprehensive experimental evaluations on different people in a
real home environment, it
is shown that the proposed fall detection system can successfully detect
different types of falls (falls
towards different orientations at different positions in a real home
environment) with small false alarms.
(i)To make the system independent from environmental features
(ii)To minimize the hand-engineered image processing steps
(iii)To make the system generic, so it works in different scenarios
Project Implementation MethodThe proposed method for the real-time human fall detection and reporting comprises of five main steps discussed as under:
Data acquisition: The first step is data acquisition which can be performed by utilizing different sensors and devices such as wearable devices, ambient sensors and video cameras.
Pre-processing: The data pre-processing step is highly important in the proposed machine learning pipeline. It consists on data filtering and scaling to remove the unwanted data and make it ready for the next steps in the methodology.
Feature extraction: Feature extraction is vital in information retrieval from any type of data. Data in its raw form don’t usually provide a better representation of the use-case. That is why, some useful features are extracted from the original data and used as input to the machine learning algorithms.
Machine learning: The machine learning (ML) models are trained in a supervised manner using the extracted features. The data is divided into training and test sets. The ML models learns about specific patterns in the training dataset about certain class.
Fall detection and reporting: The trained model are given new data in real-time and it makes decision on the basis of the gained knowledge during the training phase. The output of the model is either NORMAL or FALL. Based on the decision of the ML model, the concerned agency will be informed in case of detection of a human fall.
Benefits of the Project- It is Private and Affordable. ...
- It Provides Independence. ...
- Trained Professionals Are Always Available. ...
- They Give Peace-of-Mind. ...
- It is Highly Functional. ...
- It is Easy to Use.
The final deliverable will be a software application which will detect the fall using the ML model, the main science behind the system is image processing and machine learning.
A camera will record the data, which will be processed by the software through the code developed in Python for background subtraction, after the pre processing the software reports about the scenorio whether it is a normal case or a fall has occured.
Final Deliverable of the Project Software SystemCore Industry HealthOther IndustriesCore Technology Artificial Intelligence(AI)Other TechnologiesSustainable Development Goals Good Health and Well-Being for PeopleRequired Resources| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| Total in (Rs) | 36000 | |||
| Camera | Equipment | 3 | 10000 | 30000 |
| Battery | Equipment | 1 | 6000 | 6000 |