Classify the activity or action contained in a sequence of images from visual data sources, such as a video stream, into a set of categories using deep learning. Vision-based activity recognition involves predicting the action within a sequence of images, such as walking, swimming, or sitting, using a set of video frames. Activity recognition from video has many applications, such as human-computer interaction, anomaly detection, and surveillance. To learn more, see Getting Started with Video Classification Using Deep Learning.
Extract Video Training Data
Load Video Training Data
Design Video Classifier
|Inflated-3D (I3D) video classifier. Requires Computer Vision Toolbox Model for Inflated-3D Video Classification|
|SlowFast video classifier. Requires Computer Vision Toolbox Model for SlowFast Video Classification|
|R(2+1)D video classifier. Requires Computer Vision Toolbox Model for R(2+1)D Video Classification|
Train Video Classifier
Augment and Preprocess Training Data
Video recognition and classification, analyze, classify, and track actions contained in visual data sources.