https://store-images.s-microsoft.com/image/apps.14163.467fef53-034d-4ccc-8bcf-f2214d5bb0c3.980f4dc9-8d92-4ab2-af35-1c4dc95d8779.d29d02c1-b18f-4a8c-8794-a60b5f617532

People Segmentation

by TENSORGO TECHNOLOGIES PRIVATE LIMITED

Free trial badge

Real time detection and segmentation of the people in the image or video

Real time detection and segmentation of the people in the image or video.

In computer vision, image segmentation refers to the technique of grouping pixels in an image into semantic areas typically to locate objects and boundaries. People segmentation model is trained to detect the people in a crowd or individual locations. This model segments the people from the background scene and draws boundary boxes around each person as per their physical personalities.

Self-governing video evaluation systems have become increasingly important in recent years. There are numerous applications related to intelligent video surveillance systems such as people counting/detection, facial recognition, vehicle detection. It enables continuous monitoring of human actions which allow tagging of human body parts such as head, arms, torso and legs to achieve activity recognition tasks. The ability to track person movement in crowds through people segmentation models flourish the crowd tracking analyses and infinite possibilities while combined with other neural networks.


Use Cases

Photography Editing, Augmented Reality, Artistic Effect, Crowd Analysis, Surveillance Systems.

At a glance

https://store-images.s-microsoft.com/image/apps.60723.467fef53-034d-4ccc-8bcf-f2214d5bb0c3.980f4dc9-8d92-4ab2-af35-1c4dc95d8779.44bb99c8-d995-408c-963b-abf8255dfd15
/staticstorage/23fd3d2/assets/videoOverlay_7299e00c2e43a32cf9fa.png
https://store-images.s-microsoft.com/image/apps.60723.467fef53-034d-4ccc-8bcf-f2214d5bb0c3.980f4dc9-8d92-4ab2-af35-1c4dc95d8779.44bb99c8-d995-408c-963b-abf8255dfd15
/staticstorage/23fd3d2/assets/videoOverlay_7299e00c2e43a32cf9fa.png
https://store-images.s-microsoft.com/image/apps.60723.467fef53-034d-4ccc-8bcf-f2214d5bb0c3.980f4dc9-8d92-4ab2-af35-1c4dc95d8779.44bb99c8-d995-408c-963b-abf8255dfd15