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Face recognition in videos is a hot topic in computer vision and biometrics over many years. Compared to traditional face analysis, video based face recognition has advantages of more abundant information to improve accuracy and robustness, but also suffers from large scale variations, low quality of facial images, illumination changes, pose variations and occlusions. Related to applications, we divide the existing video based face recognition approaches into two categories: video-image based methods and video-video based methods, which are surveyed and analyzed in this paper. Unable to display preview.
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The quality of inhaler use can significantly affect the effectiveness of inhalation medications. This study was done to compare the effects of face-to-face and video-based education methods on inhaler use. Inhaler use was assessed using a item checklist before, 2 weeks, and 1 month after the education. Chi-square and independent sample t -test as well as repeated-measures analysis of variance were used for data analysis.
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Video-Based Face Recognition: State of the Art
We show several results of our method on VoxCeleb dataset. Our model takes only an audio waveform as input the true faces are shown just for reference. Note that our goal is not to reconstruct an accurate image of the person, but rather to recover characteristic physical features that are correlated with the input speech. How much can we infer about a person's looks from the way they speak? In this paper, we study the task of reconstructing a facial image of a person from a short audio recording of that person speaking.
Amazon Rekognition makes it easy to add image and video analysis to your applications. You just provide an image or video to the Rekognition API, and the service can identify the objects, people, text, scenes, and activities, as well as detect any inappropriate content. Amazon Rekognition also provides highly accurate facial analysis and facial recognition on images and video that you provide. You can detect, analyze, and compare faces for a wide variety of user verification, people counting, and public safety use cases.