Book ChapterDOI
Gesture Recognition with a 3-D Accelerometer
Jiahui Wu,Gang Pan,Daqing Zhang,Guande Qi,Shijian Li +4 more
- Vol. 5585, pp 25-38
Reads0
Chats0
TLDR
An acceleration-based gesture recognition approach, called FDSVM ( Frame-based Descriptor and multi-class SVM), which needs only a wearable 3-dimensional accelerometer and gives the best resulrs for both user-dependent and user-independent cases.Abstract:
Gesture-based interaction, as a natural way for human-computer interaction, has a wide range of applications in ubiquitous computing environment. This paper presents an acceleration-based gesture recognition approach, called FDSVM ( Frame-based Descriptor and multi-class SVM), which needs only a wearable 3-dimensional accelerometer. With FDSVM, firstly, the acceleration data of a gesture is collected and represented by a frame-based descriptor, to extract the discriminative information. Then a SVM-based multi-class gesture classifier is built for recognition in the nonlinear gesture feature space. Extensive experimental results on a data set with 3360 gesture samples of 12 gestures over weeks demonstrate that the proposed FDSVM approach significantly outperforms other four methods: DTW, Naive Bayes, C4.5 and HMM. In the user-dependent case, FDSVM achieves the recognition rate of 99.38% for the 4 direction gestures and 95.21% for all the 12 gestures. In the user-independent case, it obtains the recognition rate of 98.93% for 4 gestures and 89.29% for 12 gestures. Compared to other accelerometer-based gesture recognition approaches reported in literature FDSVM gives the best resulrs for both user-dependent and user-independent cases.read more
Citations
More filters
Proceedings Article
Activity Recognition Using Inertial Sensing for Healthcare, Wellbeing and Sports Applications: A Survey
TL;DR: In this article, the authors present the main techniques utilized, their advantages and drawbacks, performance metrics and usage examples, and discuss the research challenges, such as user behavior and technical limitations, as well as the remaining open research questions.
Book ChapterDOI
Activity recognition on an accelerometer embedded mobile phone with varying positions and orientations
TL;DR: A SVM based classifier to recognize 7 common physical activities in the natural setting where the mobile phone's position and orientation are varying, depending on the position, material and size of the hosting pocket is developed.
Proceedings ArticleDOI
Human gesture recognition using Kinect camera
TL;DR: Experimental results have shown that the backpropagation neural network method outperforms other classification methods and can achieve recognition with 100% accuracy, which confirms the high potential of using the Kinect camera in human body recognition applications.
Proceedings ArticleDOI
WiG: WiFi-Based Gesture Recognition System
TL;DR: WiG is proposed, a device-free gesture recognition system based solely on Commercial Off-The-Shelf (COTS) WiFi infrastructures and devices that stands out for its systematic simplicity, extremely low cost and high practicability.
Journal ArticleDOI
GRfid: A Device-Free RFID-Based Gesture Recognition System
TL;DR: In GRfid, after data are collected by hardware, the data is processed by a sequence of functional blocks, namely data preprocessing, gesture detection, profiles training, and gesture recognition, all of which are well-designed to achieve high performance in gesture recognition.
References
More filters
Book
An Introduction to Support Vector Machines and Other Kernel-based Learning Methods
TL;DR: This is the first comprehensive introduction to Support Vector Machines (SVMs), a new generation learning system based on recent advances in statistical learning theory, and will guide practitioners to updated literature, new applications, and on-line software.
Proceedings ArticleDOI
Advances in kernel methods: support vector learning
TL;DR: Support vector machines for dynamic reconstruction of a chaotic system, Klaus-Robert Muller et al pairwise classification and support vector machines, Ulrich Kressel.
Journal ArticleDOI
The Design and Implementation of FFTW3
Matteo Frigo,Steven G. Johnson +1 more
TL;DR: It is shown that such an approach can yield an implementation of the discrete Fourier transform that is competitive with hand-optimized libraries, and the software structure that makes the current FFTW3 version flexible and adaptive is described.
Book
An Introduction to Support Vector Machines
TL;DR: This book is the first comprehensive introduction to Support Vector Machines, a new generation learning system based on recent advances in statistical learning theory, and introduces Bayesian analysis of learning and relates SVMs to Gaussian Processes and other kernel based learning methods.
Posted ContentDOI
Making large scale SVM learning practical
TL;DR: SVM light as discussed by the authors is an implementation of an SVM learner which addresses the problem of large-scale SVM training with many training examples on the shelf, which makes large scale SVM learning more practical.