Geometry Algorithm on Skeleton Image Based Semaphore Gesture Recognition

نویسنده

  • Noriyuki Iwane
چکیده

Semaphore, a way of communicating remotely, usually practiced in scouting activities. Information is delivered by gestures or movements using specific tools such as flags, paddles or rods. Teacher and instructors are needed for learning semaphore in conventional way as they will give examples and make correction when such an error occured. Based on the practical need to provide an alternative way to learn semaphore, this research proposes the use of geometry algorithm to develop a semaphore gesture recognition based on skeleton images that read from Kinect sensor. Euclidean distance and law cosines are two formulas that applied to generate gesture parameters of each alphabet. Recognition is achieved by comparing a pair of values of model and real-time gesture. Accuracy of this system that have been measured using RMSE with 30° of tolerance yields 90.76% for Alphabet and 88% for Word.

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

تشخیص چهره با استفاده از PCA و فیلتر گابور

Methods for face recognition which are based on face structure are among techniques without supervision and produce unfavorable results in the presence of linear changes in images. PCA is a linear transform and a powerful tool for data analysis but does not produce good results for face recognition when there are non-linear changes resulting from changes in position, intensity and gesture in th...

متن کامل

Neural Network Performance Analysis for Real Time Hand Gesture Tracking Based on Hu Moment and Hybrid Features

This paper presents a comparison study between the multilayer perceptron (MLP) and radial basis function (RBF) neural networks with supervised learning and back propagation algorithm to track hand gestures. Both networks have two output classes which are hand and face. Skin is detected by a regional based algorithm in the image, and then networks are applied on video sequences frame by frame in...

متن کامل

Static hand gesture recognition using neural networks

This paper presents a novel technique for hand gesture recognition through human–computer interaction based on shape analysis. The main objective of this effort is to explore the utility of a neural network-based approach to the recognition of the hand gestures. A unique multi-layer perception of neural network is built for classification by using backpropagation learning algorithm. The goal of...

متن کامل

A Multi-scale Boosted Detector for Efficient and Robust Gesture Recognition

We present an approach to detecting and recognizing gestures in a stream of multi-modal data. Our approach combines a slidingwindow gesture detector with features drawn from skeleton data, color imagery, and depth data produced by a first-generation Kinect sensor. The detector consists of a set of one-versus-all boosted classifiers, each tuned to a specific gesture. Features are extracted at mu...

متن کامل

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

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:

دوره   شماره 

صفحات  -

تاریخ انتشار 2015