Camera-Based Object Depth Detection using OpenCV

Abstract:

This project demonstrates how a camera can be used to detect objects in real time and estimate their relative depth or distance from the camera. Using Python and OpenCV, we apply object detection and bounding box methods to highlight nearby objects and estimate how far they are. This concept can be applied to robotics, autonomous navigation, and smart surveillance systems.

Introduction:

Depth estimation is an important concept in computer vision. While advanced systems use stereo cameras or
LiDAR, it is possible to estimate object depth with a single camera using techniques like:

• Bounding Box Analysis (size vs. distance)
• Camera Calibration (focal length and reference object)
• Monocular Depth Estimation Models

In this project, we use a simple bounding box approach to estimate the distance of objects captured by a webcam.

Methodology:

1. Setup Camera Feed:

   • Access the system camera using OpenCV (cv2.VideoCapture).
   • Continuously capture frames in real time.

2. Object Detection:

   • Use pre-trained models like MobileNetSSD or YOLO for detecting objects in the frame.
   • Draw bounding boxes around detected objects.

3. Depth Estimation:

   • Assume a known real-world width of an object.
   • Use the pinhole camera model:
     Distance = (Known Width X Focal Width) / Perceived Width

4. Visualization:

   • Draw rectangles around objects.
   • Display distance labels on top of bounding boxes.

Applications:

• Robotics: Helping robots navigate obstacles.
• Autonomous Vehicles: Estimating distance of nearby vehicles/objects.
• Augmented Reality (AR): Detecting object distances for immersive AR effects.
• Security & Surveillance: Monitoring unusual proximity movements.

Conclusion:

This project shows a fundamental approach to object depth detection using a monocular camera. While not as accurate as stereo vision or LiDAR, it provides a low-cost solution for applications in robotics, surveillance, and AR. Future improvements could involve deep learning models for monocular depth estimation.

GitHub Repository:
https://github.com/Stevejerald/object-dept-detection.git