Abstract: In recent years, image and video data grows and spreads rapidly in the Internet. The data not only has huge amount, but also has the characteristics of high concurrency, high dimension and high throughput, which brings huge challenges into the real-time analysis and processing of them. To promote the image and video data processing efficiency of big data platforms, it is necessary and important to study the task of high-throughput image and video computing, and propose a series of high-throughput image and video computing theories and methods by considering the new hardware structures. Towards this end, this work first overviews previous high-throughput image and video computing theories and methods in details, and then discusses the disadvantages of the existing high-throughput image and video computing methods. Furthermore, this work analyzes three research directions of the high-throughput image and video computing task in future: the high-throughput image and video computing theories, the high-throughput image and video analysis methods, and the high-throughput video coding methods. Finally, this work introduces three key scientific problems of high-throughput image and video computing. The solutions of these problems will provide key technical support for the applications of content monitoring of Internet images and videos, the large-scale video surveillance, and the image and video search.