In order to identify the locations and types of objects in an image, computer vision models based on deep learning can be used. Here, we show two examples:
- Object detection: An artificial neural network was trained on 80,000 images. It can recognize 80 different classes of objects such as people, phones, and bananas in real time.
- Keypoint detection: This is a real-time multi-person system, which is able to jointly detect hand, facial, and foot keypoints of humans. This model was trained on 250,000 annotated instances.
Here, with a webcam connected to a powerful computer, you can experience the performance of these deep learning algorithms in a live environment.
Institute for Machine Learning, Johannes Kepler University, AUT (https://www.jku.at/iml)
Facebook AI Research, USA (https://github.com/facebookresearch/Detectron)
Carnegie Mellon University, USA (https://github.com/CMU-Perceptual-Computing-Lab/openpose)