作者: Marc Davis , Michael Smith , John Canny , Nathan Good , Simon King
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摘要: In this paper, we focus on the use of context-aware, collaborative filtering, machine-learning techniques that leverage automatically sensed and inferred contextual metadata together with computer vision analysis image content to make accurate predictions about human subjects depicted in cameraphone photos. We apply Sparse-Factor Analysis (SFA) both gathered MMM2 system results PCA (Principal Components Analysis) photo achieve a 60% face recognition accuracy people our photos, which is 40% better than media alone. short, context-aware solve problem for