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ASLLENGE. Final Project Review April 4 th , 2012. He Zhou Hui Zheng William Mai Xiang Guo Advisor: Professor Patrick Kelly. Outline. Introduction Hardware Integration Recognition Algorithm Add-on Q/A. Chart. Hardware Implementation 1.
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ASLLENGE Final Project Review April 4th, 2012 He Zhou HuiZheng William Mai Xiang Guo Advisor: Professor Patrick Kelly
Outline • Introduction • Hardware • Integration • Recognition Algorithm • Add-on • Q/A
Hardware Implementation 1 • Increasing the resistance of the flex sensor with bending • Inserting flex sensor into each glove • AD convertor captures analog signals while bending Flex Sensor Flex Sensor Glove 4
Hardware Implementation 2 • Circuitry between flex sensor gloves and AD convertor. • Impedance buffet with relation at Impedance Buffer
Hardware Implementation 3 • The Arduino Mega 2560 works as an AD converter • PC captures the signal via USB or Bluetooth • Powered by 9V battery • Digital Number Arduino Mega 2560 6
Software Integration and Bluetooth • Choosing BlueSMiRF Silver • Sending 10 digits each time from Arduino • Synced on 9600 baud rate BlueSMiRF Silver Screen Shot of Data
Hardware Testing • Flex sensors calibration • CircuitWriter Conductive Pen • Strain relief • insulation Conductive Pen
Integration • Use Data gathered from both Kinect and Finger Tracker. • Convert the data in a meaningful way to input into the database
Kinect Component • Rectangular Boxes generated around the body of the user • Whenever any of the user’s wrist move over a box, data formation begins • Break and Regenerate • Box ID is Saved • Region is Saved
Hand Component • Data Gathered from the Arduino • Data is saved whenever there is a box break using String with length 5
Levenshtein Distance Named for Vladimir Levenshtein, who devised the algorithm in 1965. Measuring the amount of difference between two sequences. Has use in Spell checking, Speech recognition, DNA analysis, and Plagiarism detection
Levenshtein Distance (cont.) Source: 1100 0110 1000 Target : 1110 0110 0010
Background Subtraction • Use Skeleton Tracking to track the human being from the depth camera. • Comparing the data streams rendered by the depth camera and the color camera. • Subtract out any pixels that don’t belong to a player.
Q&A 17