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Facial Landmarks

TENSORGO TECHNOLOGIES PRIVATE LIMITED

Facial Landmarks

TENSORGO TECHNOLOGIES PRIVATE LIMITED

Localizing human face and extracting landmarks from an image or video

Through radical computer vision techniques, the facial points of a person’s face are tracked to predict and track behaviors over the time. In the example of a facial-landmark applied on a human face, facial landmarks are a face geometry solution that estimates (x,y) location of 68 2D landmarks for each detected face in an image or a video. These key points can be used to determine a person's identification to emotions. The application draws points on detected faces and semantically links them in real time.

The facial landmarks are becoming more and more prominent intermittently to understand human psychology and their behaviors in public or private places, few countries have started identifying their citizens at various checkpoints and tracking their activities.

Use Cases
Human Emotion Classification, Human Attention Recognition, Identification, Medical Face Alignments, Other Medical Conditions.

API Request & Response
TensorGo Platform provides you with a one stop solution to customize the our API offerings as per your use case by mixing and matching the existing APIs or requesting for a new custom model. This accelerates the development of use cases with minimal or no code towards deep learning applications.

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/staticstorage/730bee6/assets/videoOverlay_7299e00c2e43a32cf9fa.png
https://store-images.s-microsoft.com/image/apps.32821.e710f382-5ddf-4949-8333-190c03deeb18.b23e26e7-b5b7-466d-841a-caa14dc0600a.47d2081c-b964-4978-bb8e-9595e57bfe27
/staticstorage/730bee6/assets/videoOverlay_7299e00c2e43a32cf9fa.png
https://store-images.s-microsoft.com/image/apps.32821.e710f382-5ddf-4949-8333-190c03deeb18.b23e26e7-b5b7-466d-841a-caa14dc0600a.47d2081c-b964-4978-bb8e-9595e57bfe27
/staticstorage/730bee6/assets/videoOverlay_7299e00c2e43a32cf9fa.png
https://store-images.s-microsoft.com/image/apps.32821.e710f382-5ddf-4949-8333-190c03deeb18.b23e26e7-b5b7-466d-841a-caa14dc0600a.47d2081c-b964-4978-bb8e-9595e57bfe27