View Proposal

Proposer
Zi Hau Chin
Title
Privacy-Preserving Classroom Occupancy Estimation Without Facial Recognition Project Purpose
Goal
Estimate classroom occupancy without identifying or tracking individuals.
Description
-What accuracy is lost when privacy-preserving transformations are applied? -Can edge processing achieve acceptable counting accuracy and latency? -How do RGB, low-resolution, depth, silhouette, or Wi-Fi approaches compare? -Does the system remain reliable under different lighting, movement, and occlusion conditions?
Resources
ESP32? Raspberry Pi 4b? People counting dataset, CounfFi, WiVi32 People COunting toolkit, OpenVINO person counting notebook...
Background
Python, computer vision and image processig, object detection, people-counting, machine learning
Url
Difficulty Level
High
Ethical Approval
Full
Number Of Students
1
Supervisor
Zi Hau Chin
Keywords
privacy-preserving computer vision, people counting, occupancy estimation, edge ai, anonymous sensing, wi-fi csi, object detection
Degrees
Bachelor of Science in Computing Science
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