Hand Gesture Recognition using fusion of SIFT and HoG with SVM as a Classifier
نویسنده
چکیده
This paper focuses on the hand gesture recognition using the various feature extraction techniques and SVM as a classifier. Her we have proposed the hybrid approach using SIFT and HoG combined as a feature extraction technique and gestures classification done using SVM linear kernel function.The accumulative multi class SVM method is employed in order to obtain a classification of the multiple gestures. In this computer age the hand gesture recognition is one of the important domain of the computer application wherein the human computer interaction is done without any contact. Various research are ongoing in order to produce the cost effective and robust system design in this field. We have also proposed our model with max 97% accuracy with 10 set of gesture. Keyword: SVM, HoG, SIFT, Hand Gesture recognition, Gesture, HC
منابع مشابه
Hand Gesture Recognition with Leap Motion
The recent introduction of depth cameras like Leap Motion Controller allows researchers to exploit the depth information to recognize hand gesture more robustly. This paper proposes a novel hand gesture recognition system with Leap Motion Controller. A series of features are extracted from Leap Motion tracking data, we feed these features along with HOG feature extracted from sensor images into...
متن کاملIndian Classical Dance Mudra Classification Using HOG Features and SVM Classifier
Received Dec 9, 2016 Revised Jun 17, 2017 Accepted Sep 17, 2017 Digital understanding of Indian classical dance is least studied work, though it has been a part of Indian Culture from around 200BC. This work explores the possibilities of recognizing classical dance mudras in various dance forms in India. The images of hand mudras of various classical dances are collected form the internet and a...
متن کاملMulti-modal Gesture Recognition Using Skeletal Joints and Motion Trail Model
This paper proposes a novel approach to multi-modal gesture recognition by using skeletal joints and motion trail model. The approach includes two modules, i.e. spotting and recognition. In the spotting module, a continuous gesture sequence is segmented into individual gesture intervals based on hand joint positions within a sliding window. In the recognition module, three models are combined t...
متن کاملHuman Computer Interaction Using Vision-Based Hand Gesture Recognition
With the rapid emergence of 3D applications and virtual environments in computer systems; the need for a new type of interaction device arises. This is because the traditional devices such as mouse, keyboard, and joystick become inefficient and cumbersome within these virtual environments. In other words, evolution of user interfaces shapes the change in the Human-Computer Interaction (HCI). In...
متن کاملCoupling Dynamic Programming with Machine Learning for Horizon Line Detection
In this paper, we consider the problem of segmenting an image into sky and non-sky regions, typically referred to as horizon line detection or skyline extraction. Specifically, we present a new approach to horizon line detection by coupling machine learning with dynamic programming. Given an image, the Canny edge detector is applied first and keeping only those edges which survive over a wide r...
متن کامل