Ishara: Touchless HCI

Real-Time Human–Computer Interface for Media Control using Hand Gestures on Edge Devices – Bharat AI-SOC Student Challenge.

Official Project Demonstration: Bharat AI-SOC Student Challenge Finalist Entry

Recognition

This project was selected as a finalist in the Bharat AI-SOC Student Challenge, demonstrating the power of Edge AI in creating intuitive, touchless user experiences.

Bharat AI-SOC Finalist List

Official Selection List: Bharat AI-SOC Student Challenge

Project Overview

Ishara is a high-performance touchless interface designed for the Bharat AI-SOC Student Challenge. It leverages advanced skeletal tracking to control media players with zero physical contact, optimized specifically for the Raspberry Pi 5.

Technical Innovations

  • MediaPipe BlazePalm Integration: Implements 21-point skeletal tracking, replacing noise-sensitive contour methods with robust 3D topology.
  • HFSM Optimization: Engineered a Hierarchical Finite State Machine to replace heavy ML classifiers, reducing CPU load to an ultra-lean 16.9%.
  • Scale-Invariant Algorithm: Uses centroid normalization, allowing seamless operation at distances up to 2.4 meters.
  • Sliding Window Median Filter: Eliminates tracking jitter, maintaining a deterministic latency of 150ms.
  • Asynchronous Execution: Utilizes Pynput for real-time HID command emulation to control VLC Media Player.
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