To train a network to recognize high fives, we need multiple examples of whatĪ high five looks like and what a high five doesn't look like. Scalogram works, but other methods may work as well. Unique and identifiable features of a high five pattern obvious. The idea here is that we're trying to create an image that will make the Will work or some other algorithm that you come up with. To this toolbox and you don't want to write the code yourself, try givingĪnother type of time-frequency visualization a shot. Note that this code uses a function called % Only run scalogram every 3rd sample to save on compute timeįb = cwtfilterbank('SignalLength', length(t), 'SamplingFrequency', fs. Plot_scale = image(zeros(224, 224, 3)) % Set up scalogramĪccel(1:end-1, :) = accel(2:end, :) % Shift values in FIFO buffer Plot_accel = plot(t, accel) % Set up accel plot T = 0:1/fs:(buffer_length_sec(end)) % Time vector % If your computer is not able to run this real-time, reduce the sample % rate or comment out the scalogram partĪ = arduino('COM3', 'Uno', 'Libraries', 'I2C') % Change to your arduinoīuffer_length_sec = 2 % Seconds of data to store in bufferĪccel = zeros(floor(buffer_length_sec * fs) + 1, 3) % Init buffer It turns out they are useful for visualizing acceleration dataįor the occasional high frequency high five within an otherwise slowly movingĪ cleaned-up version of the MATLAB code that I used to make the above plot is in Slowly varying, but then are occasionally interrupted with high frequency That is, signals that are low frequency and In particular,Ī scalogram is a time-frequency representation that is suitable for signals GoogLeNet - a network trained to recognize images. Know that I opted to convert the 3-axis acceleration data into an image to take If you watched the 4th video in the Tech Talk series on deep learning, you'll MPU9250 object, and read the accelerometer. It only takes three lines of code to connect to the Arduino, instantiate an Mpu9250 function that allows you to read the sensor with a one-line command. You to communicate with an Arduino without having to compile code for MATLAB Support Package for Arduino Hardware. To read acceleration from the MPU-9250 through the Arduino, I'm using Nice that you don't need to set up anything too fancy for this to work. With a breadboard and some jumper wires but I think it's kind of You can see that my hardware setup was pretty crudely constructed The only reason I am using this particular chip is because I already had one lying around, but anyĪccelerometer will work as long as it's small enough to be moved around Integrating the chip into my own custom circuit design, I am using aīreakout board that exposes power, ground, and the I2C communication pins. The Arduino is then connected to myįreedom inertial measurement unit from TDK InvenSense. I have an accelerometer that isĪrduino Uno through an I2C bus. So, let's get to it! An Overview of the Hardware This post is divided into the following sections: You've been sitting on for the last 10 years as well. Hopefully, youĬan use this as a starting point to solve those difficult classification problems that Of the code I wrote and the tools I used to get my high five counter working for that video. In this blog post, I will walk through the details Was the key concept that I needed for me to quickly get a high five countingĪlgorithm up and running. The topic for the 4th video in the series was transfer learning and it turned out that It was only while I was making theĭeep Learning that I realized that Deep Learning was perfect for Using the rule-based approaches to algorithm development that I was familiar Measuring the acceleration of a person's hand to count the number of times This post is from Brian Douglas, YouTube Content Creator for Control Systems and Deep Learning Applicationsįor about a decade, I've wanted to implement this silly idea I had of
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