PRE2017 4 Groep3

Group members

• Stijn Beukers
• Marijn v.d. Horst
• Rowin Versteeg
• Pieter Voors
• Tom v.d. Velden

Brainstorm

We have discussed several ideas that we may want to implement.

• An AI and GUI for a board game, in which you can play with different AIs and maybe integrate a multiplayer environment the GUI could also give tips to the users.
• A filter for notifications on your smartphone to not get distracted by non-urgent notifications while still being available for urgent notifications.
• A simple way to connect multiple interfaces like doorbells, music, notifications or your alarm to the lights in your house.
• An artificial intelligence that automatically switches between camera angles in live broadcasts.
• A program that stitches together recorded videos like vlogs automatically.
• A program that makes music compilations where music flows together naturally the way DJs mix together music as if it is one big song rather than fading in one song and starting the next.
• A system of cameras in homes for blind people that keeps track of where they have left certain items such that they can ask the system where they left it when they lose an object.
• A model of a robot which learns to walk/pick up objects using machine learning.
• A system that sorts music based on its genre.

Chosen Subject

For centuries our species has known that they are not perfect and shall never attain perfection. To get ever closer to perfection we have created many tools to bridge the gap between our weaknesses and the perfection and satisfaction we so very much desire. Though many problems have been tackled and human life has greatly improved in quality, we are still capable of losing the items that could provide such comfort. Such items could be phones, tablets or laptops. Even at home a TV remote is often lost. We propose a solution to the problem of losing items within the confinements of certain building. The solution we propose is to apply Artificial Intelligence (AI) as to find items using live video footage. This is chosen as image classifcation has been proven to be very efficient and effective at classifying and detecting images. For convenience sake this system will be provided with voice command abilities and upon finding the requested items, the system will return where the item is. This will be done via a speaker telling the user the space where the requested item is.

Goals

The goals of group 3 are as follows:

• Do research into the state of the art of AI picture recognition
• To build an AI that can effectively classify certain objects based on pictures
• Expand AI capabilities by having it classify objects correctly within video footage
• Have the AI classify objects within live camera footage
• Have the AI determine the location of an object on command and tell the user
• Have the AI remember objects which are out of sight
• Find and interview relevant users
• Determine which kind of cameras to use and where to place the cameras (in which rooms and placement)

Interviews

Possible interview questions:

• Do you often lose items in your house?
• Would you be willing to install this system in your home, if it would it be free of charge?
• If answer yes: How much would you be willing to pay for it? (if it works correctly)
• If answer is no because privacy: Ask again when you say that people get blurred on camera, or that it is not connected to the internet, or that it is like a security camera.
• How many cameras would you be willing to install?
• In which rooms would you like these cameras to be in?

Week 1

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Meeting on 23-4-2018 and 24-4-2018

• We brainstormed about several ideas for our project and chose the best one, which is described at the top.
• We discussed how to realize this project and how the wiki should look like.

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AP For 26-4-2018

Pieter

• Do research into the Users of the project

Marijn

• Do research into Tensorlow image recognition

Tom

• Do research into Environment mapping

Stijn

• Do research into voice recognition
• Fix wiki

Rowin

• Do research into privacy matter

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Meeting on 26-4-2018

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AP For 30-4-2018

Pieter

Marijn

Tom

Stijn

Rowin

Sources

Privacy:

• http://journals.sagepub.com/doi/abs/10.1177/154193120605000203 (Benefits and Privacy Concerns of a Home Equipped with a Visual Sensing System: A Perspective from Older Adults) (Smart homes, privacy and elderly)
• http://journals.sagepub.com/doi/abs/10.1177/154193120404800209 (Potential Intrusiveness of Aware Home Technology: Perceptions of Older Adults) (Smart homes and elderly)
• https://ieeexplore.ieee.org/abstract/document/6032273/ (Medical Technology in Smart Homes: Exploring the User's Perspective on Privacy, Intimacy and Trust) (Smart homes and privacy)
• http://heinonline.org/HOL/LandingPage?handle=hein.journals/valur31&div=50&id=&page= (Scowl Because You're on Candid Camera: Privacy and Video Surveillance) (Privacy and cameras)
• http://heinonline.org/HOL/LandingPage?handle=hein.journals/uhawlr27&div=17&id=&page= (Don't Smile, Your Image Has Just Been Recorded on a Camera-Phone: The Need for Privacy in the Public Sphere) (Privacy and cameras)
• https://pdfs.semanticscholar.org/87fe/3f64cff36969acbe52fce091c0c3bf8d47ce.pdf (Blinkering Surveillance: Enabling Video Privacy through Computer Vision) (Hiding identidy on cameras!)

• Polap, D., & Wozniak, M. (2017). Image approach to voice recognition. 2017 IEEE Symposium Series on Computational Intelligence (SSCI). doi:10.1109/ssci.2017.8280890 ( https://ieeexplore.ieee.org/document/8280890/ )
• Rabiner, L. R. (1990). A Tutorial on Hidden Markov Models and Selected Applications in Speech Recognition. Readings in Speech Recognition, 267-296. doi:10.1016/b978-0-08-051584-7.50027-9 ( https://ieeexplore.ieee.org/document/18626/ )
• Sarkar, M., Haider, M. Z., Chowdhury, D., & Rabbi, G. (2016). An Android based human computer interactive system with motion recognition and voice command activation. 2016 5th International Conference on Informatics, Electronics and Vision (ICIEV). doi:10.1109/iciev.2016.7759990 ( https://ieeexplore.ieee.org/document/7759990/ )
• Zhang, X., Tao, Z., Zhao, H., & Xu, T. (2017). Pathological voice recognition by deep neural network. 2017 4th International Conference on Systems and Informatics (ICSAI). doi:10.1109/icsai.2017.8248337 ( https://ieeexplore.ieee.org/document/8248337/ )