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Super Fast Real-Time Object Detection Program

Who would have imagined 10 years ago that today we would have computer programs that can differentiate moving cats from dogs in a video in matter of milli-seconds!?

Joseph Redmon works on a system called YOLO (You Only Look Once), which is an open-source method of object-detection that can super-quickly detect many sorts of objects in images and videos.
The implications of this technology can be in may fields such as self-driving cars, robotics, cancer detection and so on.
Checkout the live demo of this application in this TED talk:

YOLO: real-time object detection algorithm

How does YOLO work?

The YOLO algorithm applies a single neural network to the full image. This network divides the image into regions and predicts bounding boxes and probabilities for each region. These bounding boxes are weighted by the predicted probabilities. It is +1000x faster than R-CNN and 100x faster than Fast R-CNN. See this paper or the  YOLO website for more details on the full system.


YOLO real-time object detection demo


About Mohammad

Dr Mohammad Khazab completed his Ph.D. in Computer Systems Engineering (Artificial Intelligence) at the University of South Australia in 2011. He has worked as Senior Software Engineer, Web Developer, and Research Associate on various projects. Currently he works at Schneider Electric on the design and development of new software solutions for smart devices used for home automation and Internet of Things. He's also been working on enterprise software for supply chain network simulation and optimisation, advanced planning and scheduling. In his spare times, In his spare times, he works on creating websites and mobile applications (Web2day Design), researching and writing about cutting-edge technologies in this blog. He has ambitions to solve real-world problems, and to use his knowledge and skills to develop useful applications.

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