PRE2017 4 Groep3

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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, for example, 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 a 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 classification has been proven to be very efficient and effective at classifying and detecting objects in 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 where the requested item is.

Users

Though many people may benefit from the proposed systems, there are some people that would more so benefit from the system than others. A prime example would be people that are visually impaired or people who are blind. These people could have a hard time finding some item as they may not be able to recognize it themselves or they may not be able to see it at all. The system would provide them with a sense of ease as they would no longer have to manage where their items are all the time. Secondly, people that have a kind of dementia would greatly benefit from this system as they don't have to worry about forgetting where they left their belongings due to their deficiency. The elderly in general is also a good user for the proposed system. This is due to the fact that the elderly tend to be forgetful as their body is no longer in the prime of their life. In addition, they are also the people that also suffer the most from the aforementioned deficiencies. Additionally, smart home enthusiasts could be interested in this system is a new type of smart device. Moreover, people with large mansions could be interested in this system, as within a mansion an item is easily lost. Lastly, companies could be interested in investing in this software. Companies would by implementing the system be able to keep track of their staff's belongings and help find important documents that may be lost on someone's desk.


User Requirements

For this system to work, we need to fulfill separate requirements of the users.

  • The system should be able to inform the user where specific items are on command.
  • The system should be available at all times.
  • The system should understand voice commands and state the location of an object in an understandable manner.
  • The system should only respond to the main user for security purposes.
  • The system should take the privacy concerns of the user into respect.
  • The system should be secure.

Goals

The goals of group 3 are as follows:

  • Do research into the state of the art of AI picture recognition
  • Find and interview relevant users
  • Build an AI that can effectively classify certain objects based on pictures
  • Determine which kind of cameras to use and where to place the cameras (in which rooms and placement)
  • 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

Planning

Milestones

Object detection

  • Passive object detection (Detecting all objects or specific objects in video/image)
  • Live video feed detection (Useing a camera)
  • Input: find specific item (Input: e.g. item name. Output: e.g. camera & location)
  • Location classification (What is camera2 pixel [100,305] called?)
  • Keeping track of where item is last seen.

Voice interface

  • Define interface (which data is needed as input and output in communication between voice interface and object detection system)
  • Pure data input coupling with system that then gives output (e.g. send “find bottle” to make sure it receives “living room table” as data, without interface for now)
  • Voice parameter input (User Interface to have text input)
  • Text to speech output (Output the result over TTS)

Research

  • Check whether users actually like the system in question.
  • Check whether losing items is an actual problem for visually impaired people.
  • Check whether which locations in building are most useful for users.
  • Research privacy concerns regarding cameras in a home.
  • Analyse the expected cost.

State of the art

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


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.

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

Meeting on 26-4-2018

  • Discussed sources.
  • Specified the chosen subject, users, their requirements, goals, milestones and deliverables.
  • Made a summary for state of the art.
  • Prepared the feedback meeting.
  • Discussed interview questions

AP For 30-4-2018

Pieter

Marijn

Tom

Stijn

Rowin

Week 2

Week 3

Week 4

Week 5

Week 6

Week 7

Week 8

Week 9

Results

Sources

To cite a new source: <ref name="reference name">reference link and description</ref>
To cite a previously cited source: <ref name="reference name" \>


  1. 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)
  2. http://journals.sagepub.com/doi/abs/10.1177/154193120404800209 (Potential Intrusiveness of Aware Home Technology: Perceptions of Older Adults) (Smart homes and elderly)
  3. 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)
  4. 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)
  5. 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)
  6. https://pdfs.semanticscholar.org/87fe/3f64cff36969acbe52fce091c0c3bf8d47ce.pdf (Blinkering Surveillance: Enabling Video Privacy through Computer Vision) (Hiding identidy on cameras!)
  7. 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/ )
  8. 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/ )
  9. 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/ )
  10. 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/ )