Copyright © 2014 by Intelligent Systems Laboratory, Computer Science Department, Technion - Israel Institute of Technology, Haifa 3200003, Israel. All rights reserved


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Face Recognition Project

Face Recognition ProjectStudents: Vardan Papyan, Emil Elizarov
Instructor: Igor Kviatkovsky, Prof. Ehud Rivlin

Our goal was to create a fully operational mobile application which could detect, recognize and track human faces. In order to do that, we have decided to use the Android platform combined with the opencv library. The development of the application was made on Qualcomm MSM8960 mobile device which run a 4.0.3 Android OS. In addition to the application we have built, we also did a research about how well we can use LDA and PCA in order to recognize faces and also about the use of LDA in order to do basic pose estimation.

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Building A Non-Euclidean Roadmap From A Small Set Of Images

Building A Non-Euclidean Roadmap From A Small Set Of ImagesStudents: Alexandra Levinsky, Majd Srour
Instructor: Prof. Ehud Rivlin

In many tasks a mobile robot is required to navigate from any initial position to a desired position in its environment. This kind of task will require a global localization technique that allows the robot to operate without prior knowledge about its position and recover from odometry errors. Thus, the representation of the target position has to provide enough information for global localization. Such a representation should be robust with respect to minor changes in the environment. 

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Autonomous Navigation Based On 2-Point Correspondence Using ROS

Autonomous Navigation Based On 2-Point Correspondence Using ROSStudents: Li-tal Kupperman, Ran Breuer
Instructor: Majd Srour, Prof. Ehud Rivlin

מטרת הפרוייקט הינה הרצת אלגוריתם ניווט של רובוט למטרה מוגדרת מראש, בעזרת כלים ויזאוליים בלבד. תנועת הרובוט מתבצעת על גבי משטח מישורי, בחדר שלא מופה מראש.

 

 

 

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Troid: The Tracking Android

Troid: The Tracking AndroidStudents: Hani Assad and Shady Mansour
Instructor: Majd Srour

- Perform real time tracking using android smartphone
- The target is red colored paper, it is distinguished solely by its color
- The Smartphone controls a Rover5 robot using the microcontroller IOIO board 
 
 

 

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Fall Detection Using Color And Depth

Fall Detection Using Color And DepthStudents: Gil Ben-Ze'ev and Noam Siag
Instructor:  Amir Geva

Today a lot of people have a high probability to fall due to disease or old age. Those people need constant supervision which is very uncomfortable and expensive. In this project we've designed a fall detection algorithm that uses color and depth pictures from a Kinect camera. The robot is very user friendly and its purpose is to follow a person wherever he goes and when the person falls, the robot detects that and screams "Mayday!" for help. The fall detection algorithm uses information processing made by the follow algorithm. 

 

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