Abstract
Objectives: This research has been carried out to add interactivity and information transfer in digital format by adding technology in legacy paper based notice board system. Methods/Statistical Analysis: To achieve the above-mentioned objective, we have used Hand gesture recognition Technology. A Microsoft Kinect sensor is placed in front of the notice board to detect hand gestures which serves as the medium of interactivity. Through specified American Sign Language Number gestures user can make selections and interact with the system. For the detection of gestures Visual gesture Builder has been used which implements AdaBoost Trigger Algorithm. This framework uses Data Driven Machine Learning Algorithm to detect gestures. For the analysis, training and testing of the framework we have collected Gestures data for each predefined American Sign Language Number gestures from 0–9, from both Left and right hands, from 49 people. The machine learning algorithm was trained by 80% of the gesture data and was tested by rest 20% gestures. The approach got varying Confidence value (accuracy values) for each gesture depending on varying hand space, hand size, person’s height, clarity in gesture performance. The framework also tested based on both male and female candidates, the result for gender-based analysis is also formulated in graph. The confidence values vary from gesture to gesture for both male and female. Findings: The research come out with the results that this technique can be used to optimize and make static paper based notice boards system interactive. With this technique user is able to transfer the information or notice posted on the notice board to their digital platform by making selection and commanding using their hand gestures. This enabled the user to negotiate without changing the whole business model. Application/Improvements: This framework can be implemented on places where notice boards are used to deliver information to the users for example. Institutes, hospitals, stations etc. Using this system the user can easily interact with the notice boards and transfer information to their digital means. Keywords: Hand Gesture Recognition, Static Hand gestures, Kinect, Notice boards, Information Displays, Human Computer Interaction, VGB, Machine learning.
Highlights
In this technological era, information is the most functional and important aspect of businesses, commercial and individual use
Visual Gesture Builder (VGB) uses the clips recorded by Kinect studio
The gestures for all 0–9 American Sign Language (ASL) gestures were collected for both left and right hands from each person. 80% of the gestures were used to train the database and 20% of the gestures were used to test the trained data set in order to find if the gestures have been detected or not and by what confidence value
Summary
Information is the most functional and important aspect of businesses, commercial and individual use. Information display and transfer is an expensive process requires infrastructure and technological means. Information is displayed via two mediums: Digital and Printed means. Our focus is on the legacy way of displaying information that is Paper/Poster based notice boards. This medium has been used since long. The problems in this type of system are: People try different ways to select and carry the information. For later use people either take pictures or write the information down on paper which is not an intuitive way of transferring the information and leads to erroneous and incomplete information
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