Pedestrian Detection & Line-Crossing Tracker
Transforming CCTV Footage into Actionable Foot-Traffic Intelligence
Overview
The Pedestrian Detection & Line-Crossing Tracker automates the monitoring and analysis of pedestrian movement in CCTV video feeds. The system combines state-of-the-art object detection and multi-object tracking to accurately identify individuals, follow them across frames, and record the exact moment they cross predefined counting zones — designed for retail, transportation hubs, commercial buildings, and public spaces.
The Challenge
- Detecting pedestrians accurately in real-world CCTV footage
- Maintaining consistent tracking identities across video frames
- Counting people crossing specific virtual boundaries
- Recording precise crossing timestamps
- Supporting multiple camera configurations
- Operating efficiently on long-duration video recordings
- Exporting structured data for reporting and analysis
- Allowing non-technical users to configure counting zones without modifying code
The Solution
- YOLOv10 object detection combined with ByteTrack multi-object tracking
- Frame-by-frame pedestrian identification with persistent tracking IDs
- User-defined virtual counting lines with timestamp and direction logging
- Automatic CSV export for reporting and external system integration
- Interactive no-code line-drawing interface for zone configuration
Development Approach
Advanced Object Detection
Implemented YOLOv10 to accurately identify pedestrians across varying lighting conditions, camera perspectives, and crowd densities.
Multi-Object Tracking
Integrated ByteTrack to maintain identity consistency, minimizing duplicate counts and tracking loss.
Intelligent Event Detection
Developed line-crossing logic that records events only when legitimate crossings occur.
Flexible Camera Configuration
Created an interactive line-drawing interface allowing operators to define counting zones visually.
Long-Duration Video Processing
Optimized the pipeline to process footage in 60-second segments for efficient handling of extended recordings.
Technical Innovation — Real-Time Tracking with High Accuracy
By combining YOLOv10 detection with ByteTrack's identity association algorithms, the system achieved real-time processing, stable identity tracking, and accurate line-crossing detection with reduced false positives.
- —Real-time performance at approximately 30 FPS
- —ByteTrack pipeline with 80.3 MOTA benchmark accuracy
- —Practical deployment in accuracy-critical environments
Key Outcomes
Automated pedestrian detection and tracking implemented
Accurate line-crossing event detection achieved
Timestamp-level movement logging delivered
Interactive no-code counting zone configuration developed
CSV-based analytics export system implemented
Long-duration video processing supported
Real-time performance achieved at approximately 30 FPS
ByteTrack-based tracking pipeline delivered 80.3 MOTA accuracy
Technology Stack
AI & Computer Vision
Video Processing
Data & Analytics
Programming Language
Business Impact
The platform enables organizations to measure and analyze pedestrian movement automatically without manual observation. By converting video streams into structured behavioral data, it supports operational planning, staffing decisions, occupancy monitoring, and customer traffic measurement while significantly reducing time and cost.
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