Automated People flow tracking | with Computer Vision and AI
While detecting objects (in this case people) with Computer Vision, is nowadays common knowledge and easily accessible to anyone, tracking is still a complex task.
Tracking objects requires assigning a univocal ID to each of them (after they are detected), and keeping track of that ID until the object is on the screen.
If we fail to keep the IDs we assigned to the objects, the counting will be wrong.
I will talk in this video about the main steps to build successfully such an application and how to address the challenges step by step.
➤ Courses:
Full Computer Vision course: https://pysource.com/object-detection-opencv-deep-learning-video-course/
Training Mask R-CNN PRO (Notebook + Mini-Course): https://pysource.com/mask-rcnn-training-pro/
Blueprint: https://pysource.com/blueprint
➤ Follow me on:
LinkedIn: https://www.linkedin.com/company/pysource
➤ For business inquiries:
https://pysource.com/contact
#computervision #flowtracking #ai
While detecting objects (in this case people) with Computer Vision, is nowadays common knowledge and easily accessible to anyone, tracking is still a complex task.
Tracking objects requires assigning a univocal ID to each of them (after they are detected), and keeping track of that ID until the object is on the screen.
If we fail to keep the IDs we assigned to the objects, the counting will be wrong.
I will talk in this video about the main steps to build successfully such an application and how to address the challenges step by step.
➤ Courses:
Full Computer Vision course: https://pysource.com/object-detection-opencv-deep-learning-video-course/
Training Mask R-CNN PRO (Notebook + Mini-Course): https://pysource.com/mask-rcnn-training-pro/
Blueprint: https://pysource.com/blueprint
➤ Follow me on:
LinkedIn: https://www.linkedin.com/company/pysource
➤ For business inquiries:
https://pysource.com/contact
#computervision #flowtracking #ai
