uWave: Accelerometer-based personalized gesture recognition and its applications

By Jiayang Liu, Lin Zhong, Jehan Wickramasuriya, V. Vasudevan. Annual IEEE International Conference on Pervasive Computing and Communications, 2009

819 citations recorded by the source corpus.

Subfields: Information Systems, Human-Computer Interaction

View Paper: https://www.semanticscholar.org/paper/0ad6f6a841202fd51723b44dccabb95abc0aba87

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Information Systems

1. Adrian Perrig
2. Mohan Manubhai Trivedi
3. Benjamin M. Marlin
4. Derick A. Johnson
5. Steven Cheng-Xian Li
6. Abdullah Mueen
7. Eamonn J. Keogh
8. Harald Steck

In Human-Computer Interaction

1. Mohan Manubhai Trivedi
2. Benjamin M. Marlin
3. Derick A. Johnson
4. Steven Cheng-Xian Li
5. Sauvik Das

Citations in the corpus

• BLSTM-RNN Based 3D Gesture Classification (2013, neutral): “Liu et al. experiment with more success the DTW strategy in [9].”
• RisQ: Recognizing Smoking Gestures with Inertial Sensors on a Wristband (2014, methodology): “uWave [16] uses a dynamic time warping (DTW) technique to recognize gestures from the accelerometer present in Nintendo Wii.”
• Fast Shapelets: A Scalable Algorithm for Discovering Time Series Shapelets (2013, background): “Given these advantages, we have recently seen shapelets (and very similar ideas) applied to creating classifiers in various domains such as gesture recognition [2][17], sensor networks [12], motion capture [26], cardiology, climatology [18], robotics [26], electrical power demand [1][9] and health c”
• A scalable end-to-end Gaussian process adapter for irregularly sampled time series classification (2016, methodology): “We test the framework on the uWave data set,4 a collection of gesture samples categorized into eight gesture patterns [14].”
• Driving style recognition using a smartphone as a sensor platform (2011, methodology): “With the mounting arm, we have kept the device rotated on its side and flush with the vehicle dashboard to prevent it from moving, and to ensuring the camera is unobstructed.”
• ACCessory: password inference using accelerometers on smartphones (2012, methodology): “developed uWave–software that uses triaxial accelerometer data on mobile phones for highly accurate gesture recognition [12].”
• Logical-shapelets: an expressive primitive for time series classification (2011, background): “While shapelets were introduced only recently, they have already seen signi.cant adoption and extension in the community.”
• Generalizing DTW to the multi-dimensional case requires an adaptive approach (2016, neutral): “In paper (Liu et al. 2009) they define DTW as a dynamic programming algorithm, which calculates the matching cost and finds the corresponding shortest path.”
• The UEA multivariate time series classification archive, 2018 (2018, neutral): “The data was first described in [9].”
• Deep Learning in Human Activity Recognition with Wearable Sensors: A Review on Advances (2021, methodology): “, uWave [174]) Vary Vary Vary 107* UCI-HAR [20] Locomotion Smartphone 9D IMU 6 50 Hz 78 Ubicomp 08 [282] Home activities Proximity sensors 8 N/A 69 SHO [252] Locomotion Smartphone 9D IMU 7 50 Hz 52 UTD-MHAD1/2 [61] Locomotion & activities 3D Acc.”