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Predictive Motion Intent Estimation (Real-Time)

A real-time computer vision system that predicts object motion intent — MOVING_AWAY, CROSSING, APPROACHING, and COLLISION_RISK using optical flow, temporal feature extraction, and lightweight machine learning.

🚀 Why this project? Most vision systems detect objects. This system goes one step further by predicting motion intent, enabling early collision-risk detection — a key requirement in autonomous drones and robotics.

🧠 System Overview

  • Real-time webcam input
  • Motion detection via frame differencing
  • Optical flow for direction and speed
  • Interpretable feature extraction
  • Logistic Regression for intent classification
  • Scene-level decision aggregation for stable output

📊 Output

  • Object-level bounding boxes with intent labels
  • Single scene-level conclusion displayed on screen
  • Collision risk highlighted clearly

🛠️ Tech Stack

  • Python
  • OpenCV
  • NumPy
  • scikit-learn

▶️ How to Run bash pip install -r requirements.txt python train_model.py python main.py

About

Built a real-time computer vision system that predicts motion intent — not just motion. This project focuses on understanding behavior over time. Predicts whether objects are approaching, crossing, moving away, or pose a collision risk. Uses optical flow, temporal feature extraction, and lightweight ML and Runs in real time on a standard webcam

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