Vision Based Gesture Recognition for Alphabetical Hand Gestures Using the SVM Classifier
Journal Title: International Journal of Computer Science & Engineering Technology - Year 2012, Vol 3, Issue 7
Abstract
In this paper we discuss how a Gesture Recognition system for Alphabetical Hand Gestures is built. The main motive was to develop a system that can simplify the way humans interact with computers. The system is designed using the Support Vector Machine (SVM) Classifier which is widely used for classification and regression testing. SVM training algorithm builds a model that predicts whether a new example falls into one category or other. And the SVM classifier learns from the data points in examples when they are classified belonging to their respective categories.
Authors and Affiliations
Aseema Sultana , T Rajapuspha
Keywords
Related Articles
- EP ID EP124998
- DOI -
- Views 113
- Downloads 0
A Survey on Nanorobotics Technology
Nanorobotics is an upcoming technology field of creating robots whose components are at or close to the microscopic scale of a nanometer. To be more precise, Nanorobotics is the nanotechnology technique of building and f...
BASE STATION DRIVEN ROUTING PROTOCOL EVALUATION USING TOSSIM
Routing protocols play an important role in wireless sensor networks. There are primarily two types of protocols viz. data collection and data dissemination protocols. This paper compares two collection protocols: Base S...
Detecting The Optic Disc Using Morphology And Histogram based Thresholding
Optic disc (OD) detection is the most important step while developing an automated screening systems for certain diseases. However, it is a cumbersome task to locate Optic disc in all types of retinal images including no...
Addressing Classification Issues in Artificial Immune Network System
Immune systems have greater impact in all living creatures for their sustaining (survival) against diseases. Immune responses are triggered whenever foreign bodies invade to the body and encode attack strategies. To supp...
Computationally Efficient Segmentation Model for Collection of Images
A semisupervised optimization model for determining an efficient segmentation of many input images is proposed in this paper. The advantage of this model is twofold. Firstly, the segmentation is highly controllable as th...