Research on accident detection

by g-mastorakis in London

We did it
On 19th December 2015 we successfully raised £10 with 1 supporters in 28 days

This project aims to develop methodologies to detect accidental events such as falling, fainting, tripping over.

by g-mastorakis in London

What’s the Project about?

This study will develop methods to detect a person falling, either because of tripping over, fainting, having a heart attack, a stroke or any other event. The outcome of this study would be used to develop software to alert and promote assisted living. This would be of a particular benefit to elderly population, people who are prone to accidents and people with certain medical conditions such as low blood pressure, vertigo, heart conditions etc. that may result in a fall. 


During this study, which will last for one year, I aim to publish my work on academic journals, providing publicly the methodologies and results. There is not any financial benefit for myself or Kingston University for doing this research.

Some historical data of my research

I have studied computer science and physics and I have worked in the area of computer vision for a number of years. Some years ago (Jan 2011), I had the idea to work on a research project regarding fall detection. I was able to take a visiting position at Kingston University London for 6 months to work on this project. For the purposes of the research I used a new at the time device which could perform infrared data recording. The device was Kinect, a popular and well known Xbox game console. I was in fact one of the first machine vision scientists that used Kinect for research purposes other than gaming. Using Kinect, I could process data and with the use of my algorithms, the software was successful in identifying a particular type of fall (fall while walking). Please see the video ( for the demos. However, this research was restricted in its findings and the type of fall it could identify.

 Fall detector in action

At the end of the visiting period I published a journal paper ( which - based on Google Scholar - has more than 80 citations. The paper was on print by Springer-Verlac on 2014. Also, my work was presented on a Microsoft organised event (Kinect for Life, Oct 2012) to promote the uses of Kinect on other applications.

Phases of the process

Where will your money go?

Recently and after evaluating different Kinect devices and processing software, I discovered that my current hardware is not suitable of running those experiments. From the other hand, the University supplies hardware from a specific supplier, which unfortunately has limited flexibility in building new - custom machines. Therefore, a new laptop is needed urgently to cover the needs. A computer vision suitable laptop costs average £2000.

There are some other expenses:

Kinects 2x £100 sensors to be dismantled and mounted on the wall.

Brackets 2x £4

Other costs which are not manageable:

Commuting per year 1 £2080 off peak (40 weeks travel expenses Enfield - Surbiton)


Thank you for reading and I would be grateful for any contributions to this cause.

George Mastorakis

Visiting Researcher, SEC, Kingston University London



All I can offer as a reward is your name (if you like) to be published as part of my funders/backers on this project.


About me

George counts almost a decade in Image Processing and Machine Vision that has involved image understanding, pattern recognition and algorithmic development, having worked with established Universities and private companies. He is now a Visiting Researcher at Kingston University London, working on accident detection.

The experience and increased interest in several scientific areas (i.e. Engineering, Computer Science and Physics) has allowed him to acquire broad knowledge and abilities to apply combined and innovative thinking but also problem solving strategies using transferable skills from those scientific disciplines.



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