Intelligent Video Surveillance Using Deep Learning System
Intelligent video surveillance using deep learning system is a project that uses computer vision and deep learning techniques to automatically detect and analyze video streams from surveillance cameras. The system can be used to detect and track people, vehicles, and objects, and alert security personnel in case of any suspicious behavior or activity.
Here is a high-level overview of the project:
Data Collection: Collect a large dataset of videos from surveillance cameras in different environments. This can include both indoor and outdoor locations, and different lighting and weather conditions.
Data Preprocessing: Clean the data and extract relevant features from the video frames. This can include techniques such as background subtraction, object detection, and feature extraction.
Object Detection: Use deep learning algorithms such as YOLO or Faster R-CNN to detect and localize people, vehicles, and objects in the video frames.
Object Tracking: Use object tracking algorithms such as Kalman filters or Deep SORT to track the detected objects across different frames and camera views.
Activity Recognition: Use deep learning algorithms such as LSTM or CNN to recognize different activities such as walking, running, or carrying an object.
Alert Generation: Generate alerts when suspicious behavior or activity is detected. These alerts can be sent to security personnel or integrated with existing security systems.
Deployment: Deploy the system in the surveillance cameras and integrate it with existing security systems. This can involve providing a user-friendly interface for security personnel to monitor the video streams and respond to alerts.
Some possible enhancements to the system could include integrating it with other sensors such as microphones or temperature sensors to provide a more comprehensive surveillance system. Additionally, the system could be expanded to include facial recognition to identify known suspects or persons of interest.
- Customer are advice to watch the project video file output, before the payment to test the requirement, correction will be applicable
- After payment, if any correction in the Project is accepted, but requirement changes is applicable with updated charges based upon the requirement.
- After payment the student having doubts, correction, software error, hardware errors, coding doubts are accepted.
- On first time explanations we can provide completely with video file support, other 2 we can provide doubt clarifications only.
- If any Issue on Software license / System Error we can support and rectify that within end of the day.
- Extra Charges For duplicate bill copy. Bill must be paid in full, No part payment will be accepted.
- Online support will not be given more than 3 times.