Skip to content
AK
Back to all projects

Computer Vision

Research prototype

Autonomous Vehicle Perception System

Problem

Autonomous-driving perception requires a unified spatial understanding of the scene from several camera and sensor streams.

System

A multi-camera perception prototype that preprocesses synchronised sensor streams, extracts features, builds a bird's-eye-view representation with BEVFormer, and performs 3D object detection and tracking. Built as a research prototype for autonomous-driving perception, not a vehicle deployment.

My contribution

Built the sensor data pipeline and preprocessing stage, integrated the BEV detection model, and set up the evaluation workflow used to compare detection and tracking configurations.

System architecture

  1. Camera and sensor data
  2. Preprocessing
  3. Feature extraction
  4. BEV representation
  5. 3D detection
  6. Tracking and output

Technical focus

  • Multi-camera processing
  • 3D object detection
  • Sensor fusion
  • Object tracking
  • Real-time inference

Technology stack

  • PyTorch
  • BEVFormer
  • OpenCV
  • Python
GitHub repository for Autonomous Vehicle Perception System

Data source

Dataset and data-collection write-up is being prepared.

Data pipeline

Ingestion and preprocessing write-up is being prepared.

Model or LLM workflow

Model and workflow write-up is being prepared.

Evaluation and results

Evaluation setup and results write-up is being prepared.

Challenges and engineering decisions

Key engineering decisions write-up is being prepared.