1. Preliminary project assignment Smart house Natural User Interface for Business NUIT4B

2. Security Applications Face Recognition like a access system: Use Face tracking of Kinect. Possible programming languages: C++, C#. Possible development environment OpenCv, Microsoft Visual Studio. Need a database. ROC Applications: Open main door automatically. Denied access to certain persons to some parts of the house.

3. Security Applications Face Tracking: The Face Tracking SDK’s face tracking engine analyzes input from a Kinect camera, deduces the head pose and find several face points, and makes that information available to an application in real time. We can use the different points to compare with a face database and decide if the subject is able to access to the system.

4. Security Applications Database: We need a database with faces family for two reason: To train the system and obtain a decision threshold. To compare with family faces on real time and allow to access to the system. ROC Curves: Receiver Operating Characteristics Curves. In signal detection theory, a receiver operating characteristic (ROC), or simply ROC curve, is a graphical plot which illustrates the performance of a binary classifier system as its discrimination threshold is varied. It is created by plotting the fraction of true positives out of the total actual positives (TPR = true positive rate) vs. the fraction of false positives out of the total actual negatives (FPR = false positive rate), at various threshold settings.

5. Security Applications

6.  Detect movement and regulate the light  Possible states: light is on or off  Only human movement can control light  Movement of animals has no effect  Focus on person recognition  Predict the motion of the tracked human  turn the next lights on Motion Detection – Light Control

7.  Detect food inside the oven  Parameters of oven depends on food  Parameters:  Temperature  Modus (e.g. air circulation)  duration  Each learned food describes parameters Object recognition – oven control

8. Workflow by this example: 1. Put pizza in oven 2. Oven detect pizza via a camera 3. Adjustment with parameters  Modus air circulation  Temp.180°  Duration 10 min 4. Oven starts and ends by duration Object recognition – oven control cont.

9. Weight control: open/close curtains In the morning, when person wakes up and puts his legs on the floor, his weight on the bed becomes lighter and the curtains are opened for the new day. In the night, then person goes to sleep and his full weight is on the bed, the curtains close. *Can be also used to detect how specific person's weight has changed over the time (for example, important for people who are watching their weight).

10. Weight control: open/close curtains cont. Required software and hardware: Weighting system, connected to a bed; Connection goes to another system, that opens/closes curtains; Program, what will be used to recognize if it is the full weight of a person, or is he/she just sitting on the bed (or maybe it is a pet).

11. Weight control: starting coffee machine. The same as previous idea, when person sits on bed and the weight is changed, the signal goes to coffee machine to start producing morning coffee. *It should understand time of the day: for example if person went for a nap during the day, the curtains must close and open, but coffee machine should start only in the morning.

12. Weight control: starting coffee machine cont. Required software and hardware: Weighting system connected to the bed; Connection, that goes to the coffee machine; Program, which should identify: is it the full weight of a person; is he/she just sitting on a bed; maybe it is a pet? also take into account time of the day.

13. automatic rescue call: detection of a person which lie on the ground Domotics can be applied to healthcare. There are several situation where automatic rescue call can be helpful For example: -The patient grabs his ribs swiftly. -The patient lays on the ground for a long period.

14. The idea is to send a warning message to the one who is taking care of patients when some symptoms are detected. The warning system can be connected to some receiver like the mobile phone. Aditional information can be send with the warning to allow better answers. automatic rescue call: detection of a person which lie on the ground

15. automatic rescue call: detection of a person which lie on the ground One application of automatic rescue call is detection of a person which lie on the ground. Kinect can be used to recognise the possition of the body to detect if its lies horizontally. It can have problem recognising when is a real healthcare problems or if it lies voluntary on the ground. Machine learning can be used to get better results.

16. Kinect Interaction with devices without the use of any controller Based around a webcam- style add-on peripheral, it enables users to control and interact with their console/computer without the need for a controller, through a natural user interface using gestures and spoken commands. Programming language: Visual Basic, C#, C++. Kinect for Windows Software Development Kit (SDK): the SDK provides the tools and APIs, both native and managed, that you need to develop Kinect-enabled applications for Microsoft Windows.

17. The idea is to use body movements to control devices and objects: gestures to turn on and turn off the television and changing channels; gestures to open and close curtains; other possible applications on other devices. Kinect

19. Skeleton tracking by Kinect Skeletal Tracking is optimized to recognize users standing or sitting, and facing the Kinect; To be recognized, users simply need to be in front of the sensor, making sure the sensor can see their head and upper body; There is a Kinect field of view of the users determined by the settings of the IR camera; The infrared emitter of a Kinect sensor projects a pattern of infrared light. This pattern of light is used to calculate the depth of the people in the field of view allowing the recognition of different people and different body parts.

20. Speech recognition One of the most 'used biometrics for authentication is the recognition of the voice. Not only the tone, but also the tone or the speed at which we speak. This technology is catching on in various fields of application, being considered one of the most 'safe and efficient in terms of security. The conversion from speech to text involves a series of complex steps: In the first place, the ADC (analog-digital converter) converts the sound recorded in digital form, in order to make it compatible with the computer. The quality of the conversion from analog to digital is very dependent on the sampling frequency of the system. During the conversion, you filter the noise that the microphone has picked up the item and adjust the levels of sound and volume at a constant level. After this, the digital data then undergo a series of "splicing" a confrontation with the terms of the database of voice recognition software, in order to accurately transcribe the audio files into text.

21. The speech recognition should be: speaker dependent : it recognizes just the voice, with its specific tone,of just one user; speaker independent: it is for a generic spoken. The operation of a speech recognition system is based on the comparison of the input, properly prepared, with a database created in the training phase of the system. The application software tries to find the word spoken by the speaker, looking in the database a sound similar, and checking the corresponding word. Speech recognition