Back to all projects
Computer Vision
Smart Traffic Analytics System: Vehicle Detection and Tracking
Detecting and tracking vehicles in real-time video streams for traffic analysis or autonomous driving.
Project Overview
A computer vision project focused on identifying and following vehicles in video footage, essential for smart city applications and advanced driver-assistance systems.
Technologies Used
PythonOpenCVYOLODeep Learning
Methodology
- 1Utilizing object detection models (e.g., YOLO, SSD) for vehicle localization.
- 2Implementing multi-object tracking algorithms (e.g., DeepSORT, ByteTrack).
- 3Counting vehicles, analyzing traffic flow, and estimating speed.
- 4Handling occlusions, varying vehicle types, and environmental conditions.
More in Computer Vision
Handwritten Digit Recognition
Classifying handwritten digits from the MNIST dataset using Random Forest ensemble learning.
Real Time Object Recognition
Detecting and tracking moving objects in video streams using computer vision techniques.
AI powered Face Detection and Tracking
Implementing real-time face detection and tracking in video feeds.