Motion Type Detection Using Accelerometer & Machine Learning
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I am about to embark on development of a mobile app that uses the accelerometer to detect motion type, whether it's jumping, running, walking, etc. Now I have done a lot of online searching recently and somewhat understand that using machine learning is possible to detect patterns in sample data collected from accelerometer. I am totally new to machine learning but if I understand correctly (based on the hints other experts have given online) I can use either Support Network Machines or Neural Networks to recognize the patterns in the collected samples and map it to a specific movement type. I also know OpenCV library provides both methods. 

Can someone with expertise in the field tell me which method is better to use and also guide me through the steps required from data collection down to result presentation?