Hand gesture recognition supported by fuzzy rules and Kalman filters

نویسندگان

  • Michal Lech
  • Bozena Kostek
چکیده

The paper presents a system based on camera and multimedia projector enabling a user to control computer applications by dynamic hand gestures. Gesture recognition methodology based on representing hand movement trajectory by motion vectors analysed using fuzzy rule-based inference is first given. For effective hand position tracking Kalman filters are employed. The system engineered is developed using J2SE and C++/OpenCV technology. In addition, OpenCV is used for image processing and J2SE with jFuzzyLogic package is employed for gesture interpretation. Results of fuzzy rule-based and fixed threshold-based gesture recognition effectiveness are provided. Additionally, for fuzzy rule-based gesture recognition the system efficacy after utilising Kalman filters is examined. The so-called interactive whiteboard application is given as an example of the system usage.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Applying mean shift and motion detection approaches to hand tracking in sign language

Hand gesture recognition is very important to communicate in sign language. In this paper, an effective object tracking and hand gesture recognition method is proposed. This method is combination of two well-known approaches, the mean shift and the motion detection algorithm. The mean shift algorithm can track objects based on the color, then when hand passes the face occlusion happens. Several...

متن کامل

A fuzzy rule-based approach to spatio-temporal hand gesture recognition

Gesture-based applications widely range from replacing the traditional mouse as a position device to virtual reality and communication with the deaf. In this paper, we present a fuzzy rule-based approach to spatio-temporal hand gesture recognition. This approach employs a powerful method based on hyperrectangular composite neural networks (HRCNNs) for selecting templates. Templates for each han...

متن کامل

Hand Gesture Recognition from RGB-D Data using 2D and 3D Convolutional Neural Networks: a comparative study

Despite considerable enhances in recognizing hand gestures from still images, there are still many challenges in the classification of hand gestures in videos. The latter comes with more challenges, including higher computational complexity and arduous task of representing temporal features. Hand movement dynamics, represented by temporal features, have to be extracted by analyzing the total fr...

متن کامل

Real-Time Hand Tracking and Gesture Recognition System

In this paper, we introduce a hand gesture recognition system to recognize real time gesture in unconstrained environments. The system consists of three modules: real time hand tracking, training gesture and gesture recognition using pseudo two dimension hidden Markov models (P2-DHMMs). We have used a Kalman filter and hand blobs analysis for hand tracking to obtain motion descriptors and hand ...

متن کامل

Model-based Gesture Recognition

We describe a new technique for gesture recognition that involves both physical and control models of gesture performance. The technique incorporates an underlying model of the physical motion involved with performing a specific gesture. The gestures we analyze are all made with simple motions of the right arm, and we track only the hand position. We model the actual path the hand traverses whi...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:
  • IJIIDS

دوره 6  شماره 

صفحات  -

تاریخ انتشار 2012