Goal or No Goal, that is the question

The Goal-Line system can track the motion of the ball up to 500 images per second. The supporting computer vision software tracks the movement of all objects on the pitch in all the images and filters out the players, referees and all disturbing objects.

How augmented reality will change sports

Chris Kluwe wants to look into the future of sports and think about how technology will help not just players and coaches, but fans. Here the former NFL punter envisions a future in which augmented reality will help people experience sports as if they are directly on the field — and maybe even help them see others in a new light, too.

DeepFace: Facebook's face verification algorithm

The Facebook team adopted Deep Learning to apply to their face verification algorithm in lieu of well engineered features which is common in majority of contributions in this field.

Stephen Wolfram introduces the Wolfram Language

For image processing and computer vision applications, the Wolfram Language provides built-in support for both programmatic and interactive modern industrial-strength image processing—fully integrated with the Wolfram Language's powerful mathematical and algorithmic capabilities.

Revolutionizing the face of sports using computer vision

Primarily, the system works through the aid of six motion-capture cameras equipped with computer vision throughout the arena. These six synchronized cameras were divided into three per half-court areas. The cameras are programmed to take 25 images per second and record them in its memory for review by sports analytics.

Plankton Portal: Crowdsourced classification of Plankton images

The imaging system on ISIIS is a high definition shadow imaging system that provides intensely magnified view of tiny underwater organisms in the visible light spectrum. In addition to its non-destructive nature compare to the traditional sampling methods, the development of ISIIS has lead to unprecedented data production.