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Computer Vision
AI powered Face Detection and Tracking
Implementing real-time face detection and tracking in video feeds.
Project Overview
Developing a system to accurately detect human faces in images and video streams, and subsequently track their movement across frames.
Technologies Used
PythonOpenCVHaar CascadesDeep Learning
Methodology
- 1Utilizing pre-trained Haar cascades or deep learning models (e.g., MTCNN).
- 2Implementing bounding box generation and non-maximum suppression.
- 3Applying tracking algorithms (e.g., KCF, CSRT) for persistent tracking.
- 4Optimizing for real-time performance and varying lighting conditions.
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