AIComputer VisionResearch2024

RGB, IR Multi-Modal Fusion

An advanced computer vision system that fuses RGB and infrared imaging for enhanced object detection and recognition in challenging environmental conditions.

Project Overview

This research project develops a multi-modal fusion approach combining RGB and infrared (IR) imaging to improve object detection accuracy in low-light and adverse weather conditions. The system leverages deep learning techniques to intelligently fuse complementary information from both modalities, achieving superior performance compared to single-modal approaches.

Architecture Diagrams

RGB, IR Multi-Modal Fusion - System Architecture

Key Features

Real-time fusion of RGB and IR image streams

Deep learning-based feature extraction and fusion

Enhanced object detection in low-light conditions

Robust performance in fog, smoke, and adverse weather

Adaptive fusion weights based on environmental context

Support for multiple fusion architectures (early, late, hybrid)

Images

RGB, IR Multi-Modal Fusion - Screenshot 1

RGB, IR Multi-Modal Fusion - Screenshot 2

Technology Stack

Backend

PythonPyTorchOpenCV

Frontend

FlaskJavaScriptWebRTC

Database

SQLite

Tools & Platforms

CUDATensorRTNumPyGit

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