Complex Gesture Recognition using Coupled Switching Linear Model
نویسندگان
چکیده
We present a method coupling multiple switching linear models. The coupled switching linear model is an interactive process of two switching linear models. Coupling is given through causal influence between their hidden discrete states. The parameters of this model are learned via EM algorithm. Tracking is performed through the coupled-forward algorithm based on Kalman filtering and a collapsing method. A model with maximum likelihood is selected out of a few learned models during tracking. We demonstrate the application of the proposed model to tracking and recognizing two-hand gestures
منابع مشابه
Recognition of Two-Hand Gestures Using Coupled Switching Linear Model
We present a method for recognition of twohand gestures. Two-hand gestures include fine-grain descriptions of hands under a complicated background, and have complex dynamic behaviors. Hence, assuming that two-hand gestures are an interacting process of two hands whose shapes and motions are described by switching linear dynamics, we propose a coupled switching linear dynamic model to capture in...
متن کاملTwo-Hand Gesture Recognition using Coupled Switching Linear Model
We present a method coupling multiple switching linear models. The coupled switching linear model is an interactive process of two switching linear models. Coupling is given through causal influence between their hidden discrete states. The parameters of this model are learned via EM algorithm. Tracking is performed through the coupled-forward algorithm based on Kalman filtering and a collapsin...
متن کاملEMG-based wrist gesture recognition using a convolutional neural network
Background: Deep learning has revolutionized artificial intelligence and has transformed many fields. It allows processing high-dimensional data (such as signals or images) without the need for feature engineering. The aim of this research is to develop a deep learning-based system to decode motor intent from electromyogram (EMG) signals. Methods: A myoelectric system based on convolutional ne...
متن کاملEstimating Stock Price in Energy Market Including Oil, Gas, and Coal: The Comparison of Linear and Non-Linear Two-State Markov Regime Switching Models
A common method to study the dynamic behavior of macroeconomic variables is using linear time series models; however, they are unable to explain nonlinear behavior of the series. Given the dependency between stock market and derivatives, the behavior of the underlying asset price can be modeled using Markov switching process properties and the economic regime significance. In this paper, a two-...
متن کامل