Job

Internship | Deep learning for anomaly detection in videos

Finding anomalous events in videos by unsupervised spatio-temporal deep learning.

Location

Den Haag

Education type

university (wo)

Type

Internship and graduation project

Hours a week

Fulltime – 40

Interested?

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What will you be doing?

Relevance
For many applications, it is important to know when particular events happen. For instance, a person that collapses on the ground. Or, a person becoming aggressive. The goal is to detect such events of interest.

Problem
For deep learning, typically, such events are annotated by a human to get the groundtruth labels. For video data, this costs a lot of time. For each frame one or more annotations are needed, in the form of a bounding box, which is a tedious task. Moreover, for each type of event, many annotations are required to learn a good model. There can be many of such events of interest.

Approach
A different approach is to consider the events of interest as ‘standing out of the ordinary’, i.e., anomaly detection. Typically the events of interest are rare, or, in other words, ‘anomalies’. Given that most of the data is ‘normal’, a model may learn about all the usual but uninteresting events. The idea is that the model does not fit accurately when an anomalous event happens. An example of such a model is an auto-encoder, which makes a reconstruction error for samples which it did not see during training.

Assignment
Your assignment is to create a video-based anomaly detection. There is a lot of research to base on. Your this assignment is to tailor an algorithm such that it can detect and localize anomalies in videos where multiple people are present in the scene.

What do we require of you?

We require you to have knowledge of Python and Deep Learning. Also preferred, but not necessary is knowledge of Keras.
The internship will start on August 1st at the earliest.

What can you expect of your work situation?

TNO is an independent research organization whose expertise and research make an important contribution to the competitiveness of companies and organizations, to the economy and to the quality of society as a whole. Innovation with purpose is what TNO stands for. With 3000 people we develop knowledge not for its own sake but for practical application. To create new products that make life more pleasant and valuable and help companies innovate. To find creative answers to the questions posed by society. We work for a variety of customers: governments, the SME sector, large companies, service providers and non-governmental organizations. Working together on new knowledge, better products and clear recommendations for policy and processes. In everything we do, impact is the key. Our product and process innovations and recommendations are only worth something if our customers can use them to boost their competitiveness.

The Intelligent Imaging research group is a young, passionate and creative group of professionals (40 people) specialized in the development of groundbreaking applications in the fields of computer vision and deep learning. One third of the group has started working for us in the past four years.

What can TNO offer you?

You want to work on the precursor of your career; a work placement gives you an opportunity to take a good look at your prospective future employer. TNO goes a step further. It’s not just looking that interests us; you and your knowledge are essential to our innovation. That’s why we attach a great deal of value to your personal and professional development. You will, of course, be properly supervised during your work placement and be given the scope for you to get the best out of yourself. Naturally, we provide suitable work placement compensation.

Application process

For this vacancy it is required that the AIVD issues a security clearance after conducting a security screening. Please visit for more information the AIVD website.

Has this vacancy sparked your interest?

Then please feel free to apply on this vacancy! For further questions don’t hesitate to contact us.


Contact: Wouter Uijens
Phone number: +31 (0)6-158 87391



Note that applications via email and third party applications are not taken into consideration.

Interested?

Apply now

Apply

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