VR based Ice-Hockey Game
using advanced Computer Vision Techniques


This project creates an immersive virtual reality ice-hockey game using advanced computer vision techniques. Real-time analysis of video streams detects players, pucks, and the game arena. Pose estimation captures natural player movements, while OCR extracts player details for realism. The result is an engaging VR experience where players can authentically interact with ice-hockey action.


Real-time Video Analysis:
Detecting players, pucks, and the game arena in real-time requires efficient processing to avoid performance issues and delays.
Natural Player Movement:
Accurately capturing authentic player movements from video frames while accounting for camera angles and obstructions is a challenge.
Accurate 3D Realism:
Converting 2D player poses to precise 3D coordinates without sacrificing spatial accuracy is essential for a realistic VR experience.


Data Annotation Expertise:
A skilled team annotates 2D video frames to ensure top-quality training data, enhancing CNN-based pose prediction.
Optimized Libraries:
Utilizing OpenCV and the JDE Tracker improves object detection and tracking speed, resulting in smoother VR gameplay.
CNN-powered Pose Estimation:
CNNs trained on annotated data enhance player movement realism, enriching the VR experience.
Mathematical 3D Conversion:
Developed mathematical models accurately transform 2D poses into 3D coordinates, elevating spatial realism in the VR game.

Development Process











Sales & ROI

As a result of the new properly designed website, our client FINews, was able to engage with the
audience well and close more sales in a short span of 2 months. They gained the ROI after 3
months with our assistance.


Conversion rate
in 2022


Increase in monthly

Team & Role

A dedicated team of 12 individuals contributes their expertise to this project, including:
  • Two Data Science Engineers
  • Data Collection and Cleaning Specialists
  • UI/UX Designers
  • Blockchain Experts
  • Backend and Frontend Engineers

Tools / Technologies

The project leverages a robust technology stack to ensure efficient performance and reliability.




JDE Tracker


Text Spotting


FINews’s objective was to build a user-friendly and aesthetically pleasing website that would
encourage greater traffic and sales. Deline Media was able to develop a user-friendly and
responsive website for them which enabled their customers to explore the capital market and
current forex rates fast enough.

Technical Achievements

Frame Annotation by Dedicated Labelers:
A specialized team annotates frames of the 2D video, highlighting player poses. We have extensive experience in data labeling and cleaning, ensuring training data quality for image-based and NLP-based tasks.
CNN Training for Pose Prediction:
Through CNN training on annotated data, we’ve developed a pipeline that predicts player poses based on input images.
3D Coordinate Transformation:
Mathematical models have been created to transform 2D poses (detected by CNNs) into accurate 3D coordinates, enhancing spatial realism.

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New York, USA
Lahore, Pakistan
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