Laura Bravo Sánchez
PhD Candidate, Department of Biomedical Data Science, Stanford University
Talk Title: How can Computer Vision guide the understanding of parent-child interactions?
Abstract: Understanding Parent-Child Interactions (PCI) is crucial for child development specialists, who rely on video as a primary tool in controlled and naturalistic settings to test their hypothesis. However, the increasing volume of video data poses challenges for manual analysis. In response, our research at the Stanford Medical AI and Computer Vision Lab is dedicated to developing Computer Vision techniques that both unlock the full potential of video data and streamline labor-intensive processes. This talk delves into the Computer Vision approaches tailored to PCI studies that we have been working on. We explore how our work aims to bridge the gap between the intrinsic subtleties of human behavior and the limitations of current 3D monocular human mesh recovery methods
Bio: Laura is currently a PhD Candidate in the Department of Biomedical Data Science at Stanford University. She is advised by Prof. Serena Yeung-Lévy and is supported by the Fulbright Minciencias Colombia Fellowship. Her research focuses on understanding human behavior through Computer Vision. In particular, she works on improving modeling of 3D human poses and interactions in video for parent-child interactions. Prior to her doctoral studies, she received her BSc. and MSc. from Universidad de los Andes in Colombia, where she worked on employing Computer Vision for surgical videos
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