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This article explains how front‑end developers can run AI locally on web, Android, iOS and Raspberry Pi devices using TensorFlow Lite MoveNet for real‑time pose estimation, walks through setup, model variants, Python code examples, and practical applications such as yoga‑pose classification.
The presentation explains AR fundamentals, distinguishes it from AI and VR, and details a shoe‑try‑on system that captures 30 fps video, uses AI key‑point detection and pose estimation to overlay 3D shoe models—created via manual, scanning, or photogrammetry methods—rendered with GPU pipelines and PBR, enhanced by green‑screen occlusion and shadow techniques, earning positive audience feedback.
The talk describes Youku’s intelligent production platform, which uses AI and cloud computing to automatically analyze video frames, extract fine‑grained metadata such as scenes, persons, actions and scores, and then generate highlights, vertical clips, annotations and feedback for editors and upstream producers, while addressing challenges like pose‑tracking, graph‑based action classification and future plans for deeper video understanding and open competitions.