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Jayachandra Dakala, Technical Architect at PathPartner Technology, presents the “Understanding and Implementing Face Landmark Detection and Tracking” tutorial at the May 2018 Embedded Vision Summit.

Face landmark detection is of profound interest in computer vision, because it enables tasks ranging from facial expression recognition to understanding human behavior. Face landmark detection and tracking can be quite challenging, though, due to a wide range of face appearance variations caused by different head poses, lighting conditions, occlusions and other factors.

In this tutorial, Dakala introduces face landmarks and discuss some of the applications in which face landmark detection and tracking are used. He also highlights some of the key challenges that must be addressed in designing and implementing a robust face landmark detection and tracking algorithm. He surveys algorithmic approaches, highlighting their complexities and trade-offs. He concludes with a discussion of implementation approaches for a real-time embedded face landmark tracking system.

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