Machine Learning on Video
Factors like cheaper bandwidth and storage, expanded remote work, streaming entertainment, social media, robotics and autonomous vehicles, all contribute to the rapidly increasing volume of video data. Nonetheless, performance in benchmark ML video tasks in perception, activity recognition, and video understanding lag behind the image counterpart. In this post, we consider the challenges in applying ML to video while surveying some of the techniques en vogue to address them. The Time Dimension Treating video analytics as a search over space and time, the dimensionality begets additional hurdles to statistical and computational efficiency....