Computer Vision News - February 2019

10 Computer Vision News Project Management Tip Management Artificial Intelligence is impacting the automotive industry in more than one way. Of course, by developing self- driving cars , which might completely change our travel experience in only a few years. But also in many other ways: think at driving assistance tools , using sensors of one kind or another; driver monitoring , enabling to increase security by monitoring the driver’s behavior; and many more driving and security features, some of which have to be invented yet. The project manager has to take into account the huge complexity of this new field and the colossal resources that it requires (for instance in terms of road testing and annotated data). Many startups are entering the industry, hoping to find a successful way to implement AI in the automotive industry . Many of them employ capable and skilled workers, who still lack the needed training to do their job in this new field. They do not know the techniques and they do not know the terminology. The most probable result is a lot of energy and time going to waste. My recommendation to these companies, in particular to the project managers and to computer vision engineers, is to avoid reinventing the wheel: they should properly understand the importance of making the first steps in this field only after learning the basics from those who are already engaged in it . I can bring a very appropriate example from our successful experience at RSIP Vision : the company has sent very early a group of computer vision engineers (which included myself) to the Self- Driving Car Engineer Nanodegree program offered by Udacity , one of the best programs that teaches the right skills and prepares for a fruitful work in the field of autonomous systems. This program is a practical course, built in cooperation with Waymo (Google) , Uber , Mercedes and others. It enables to learn the theoretical background, as well as working hands on practical tools and on writing the algorithms, using the deep learning neural networks in Python and C++. This results in the engineer’s readiness to work very efficiently in any of the many projects which are being carried on in the AI for autonomous vehicles arena. Deep learning, sensor fusion, LiDAR data and other important components of this work will be precious in a very large range of applications and products. Learning the Right Skills for Autonomous Systems RSIP Vision’s CEO Ron Soferman has launched a series of lectures to provide a robust yet simple overview of how to ensure that computer vision projects respect goals, budget and deadlines. This month Ilya Kovler tells us about Learning the Right Skills for Autonomous Systems Projects . It’s another tip by RSIP Vision for Project Management in Computer Vision . “Learn the basics from those who are already engaged”