Development of Surveillance Framework for Person Localization and Recognition in UAV Images
In recent years, use of UAV is increasing for aerial surveillance, border patrol and convoy protection, tracking a ground-moving target (GMT) autonomously. However, the Ariel images have an issue of cluttered background, low resolution quality and various environment and lighting conditions which in
2025-06-28 16:32:06 - Adil Khan
Development of Surveillance Framework for Person Localization and Recognition in UAV Images
Project Area of Specialization Artificial IntelligenceProject SummaryIn recent years, use of UAV is increasing for aerial surveillance, border patrol and convoy protection, tracking a ground-moving target (GMT) autonomously. However, the Ariel images have an issue of cluttered background, low resolution quality and various environment and lighting conditions which increase complexity levels of localization and recognition. In this project, we are focusing to implement human localization, recognition, and tracking in UAV real-time images and video with various constraints. The main components of the project will be: (1). UAV Platform for video and image acquisitioning, (2) Data link for transferring of image from UAV to processing system (3) Development and use of algorithms for image enhancement, features extraction for human detection and recognition, and performance comparison of algorithms. (4) Implementation on Raspberry-PI that can be used as onboard processing on UAV. (5) We will collect local environment large dataset for better accuracy.
The proposed system will be utilized for security surveillance, crowd management, and also for delivery services.
Project ObjectivesThere are following objectives of human localization and recoginition from aerial images:
- UAV Platform for Video and Image acquisitioning
- Human Detection in Aerial images and video
- Crowd counting and management through UAV aerial images
- Datalink for transmission of video from UAV to ground control system.
- Collection of 20k aerial images from different clutter backgrounds.
- Performance Comparison of Acquired image (Still) and on move.
- Impementation on Raspberry PI.
Fig 1: Objectives of human localization and recognition in UAV Images
There are following steps for project implementation:
- UAV directly communicate with drone and raspberry-pi
- Video obtain on both remote and raspberry pi
- Aerail Images sepration from video
- Pre-proceing and image enhancment
- Extraction of area of interst
- Human features extraction
- Human detection
- Human counting
- Display detected and counted aerial images/video on screen
Fig 2: Implementation model of human localization and recognition in UAV Images
Fig3: Flow Chart of human localization and recognition in UAV Images
Benefits of the Project• In recent years, use of UAV is increasing for aerial surveillance, border patrol and convoy protection, tracking a ground-moving target (GMT) autonomously
• An Unmanned Aerial vehicle (UAV) is a robot used to augment human capability in both civil and military activities. • The Human detection and recognition are used in following aeras:
- Identify criminals
- Crowd managment
- safe city concept
- traffic control system
- flood disaster monitoring
- rescue operations
- surveillance and monitoring etc.
-UAV Video/Image Acquisitioning Platform
Camera Resolution 1280x720
Camera Resolusion 640x260
ON-board and ground control system for UAV
-Software for image enhancement, features extraction, and human detection in images
For Image enhancement using Gussian, sobal and canny edge detector.
For features extraction and human detection using Haar- Cascade, Tamplet matching, YOLO and CNN.
-Raspberry-PI based processing platform that can be ultilized both at onboard and ground system
Lunix based operating system
Used for Image Processing, and real time person detection and regonition.
Final Deliverable of the Project HW/SW integrated systemCore Industry SecurityOther Industries Transportation Core Technology Artificial Intelligence(AI)Other Technologies Internet of Things (IoT)Sustainable Development Goals Sustainable Cities and CommunitiesRequired Resources| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| Total in (Rs) | 69850 | |||
| 450 quadcopter frame | Equipment | 1 | 2050 | 2050 |
| Quadcopter legs | Equipment | 1 | 450 | 450 |
| Radiolink T8FB | Equipment | 1 | 8000 | 8000 |
| APM 2.8 flight controller | Equipment | 1 | 16500 | 16500 |
| Gens 4000 45c 3s LiPo battery | Equipment | 1 | 9200 | 9200 |
| 30A Escs | Equipment | 4 | 1250 | 5000 |
| A2212 1000kv motors | Equipment | 4 | 1100 | 4400 |
| B6 Charger | Equipment | 1 | 3050 | 3050 |
| 10 X 4.5 props set | Equipment | 2 | 350 | 700 |
| Rf7 simulator | Equipment | 1 | 2300 | 2300 |
| Power module for Raspberry Pi | Equipment | 1 | 1000 | 1000 |
| Raspberry Pi | Equipment | 1 | 6000 | 6000 |
| Pi camera | Equipment | 1 | 1200 | 1200 |
| equipment required for assembling(e.g wires, solder iron etc) | Miscellaneous | 5 | 2000 | 10000 |