International Journal of Innovative Science and Modern Engineering (IJISME) ISSN: 2319-6386, Volume-3 Issue-2, January 2015 57 Published By: Blue Eyes Intelligence Engineering & Sciences Publication Retrieval Number: B0788013215/2014©BEIESP Implementation of an Intelligent Head Gesture Recognition System Rushikesh T. Bankar, Suresh S. Salankar Abstract - As per the rapidly advancement in the changing technology, the numerous applications are required. For example, for face, hand and gesture recognition. The previous researchers have been developed various methods foe head gesture recognition and they presented various limitations. Therefore the paper proposes an FPGA based gesture recognition system. The gesture detection and gesture recognition can achieve 30 frames per second using FPGA system. Accordingly that the system software can subsequently schedule all the tasks during the processing. The proposed system also introduces the obstacle detection technique. The system uses ultrasonic sensors for the obstacle detection. The proposed system is responsible for the detection of obstacles. Index Terms - Wheelchair Interface, Ultrasonic Sensors, Face Detection, Gesture Recognition. I. INTRODUCTION The wheelchair is one of the most commonly method for enhancing the personal mobility of the users or peoples or the individuals with the certain disabilities. As per the world health organization, the total estimated count 1 % of the world’s population or just over the 65 million people or user or individuals need a wheelchair. Over the 6.1 million people in India have movement related disability. The evolution of the User Interface (UI) witnessed the development from text based UI based on keyboard to GUI based on mice. In current virtual environments applications, keyboards, mice, and joysticks are still the most popular and dominant devices. However, they are inconvenient and unnatural. The use of human movements, especially head gestures, has become an important part of HCII (Human Computer Intelligent Interaction) in recent years, which serves as a motivating force for research in modelling, analysing and recognition of head gestures. Many techniques developed in HCII can be extended to other areas such as surveillance, robot control and teleconferencing. Recognizing Gestures is a complex task which involves many aspects such as motion modelling, motion analysis, pattern recognition and machine learning. The successful deployment of the intelligent system relies on their high performance as well as low cost. Manuscript Received on January 2015. Prof. Rushikesh T. Bankar, Asst. Prof., Department of Electronics & Telecommunication Engineering, G. H. Raisoni College of Engineering, Nagpur, India. Dr. Suresh S. Salankar, Prof., Department of Electronics & Telecommunication Engineering, G. H. Raisoni College of Engineering, Nagpur, India. As compared to the other head gesture recognition system, the main performance of the intelligent system includes the autonomous navigation capability for good safety, flexibility, mobility, obstacle avoidance etc., an intelligent system including voice based control system, vision based control system, and sensor based control system. The new generation, an intelligent system of head gesture recognition should be able to deal with the uncertainties from the practical applications point of view. They are the user head either out of the image view or only the profile face is in the captured image, the face color of the user is user dependent, or may change dramatically in the varying illumination conditions, the different facial appearances conditions of the user, such as mustache and glasses, and the cluttered background. The proposed system is an intelligent system for the head gesture recognition, which is based on the combination of Adaboost and improved camshift algorithms. II. HUMAN GESTURE REPRESENTATION There have been many studies on human gestures in psycholinguistic research. K. Yuan [1] represents the Head Gesture Recognition for Hands Free Control of An Intelligent Wheelchair. In this paper, a novel integrated approach to Real - Time Face Detection, Tracking and Gesture Recognition is proposed, namely Head Gesture Based Interface (HGI). It is to be used as the Human Robot Interface for the Intelligent Wheelchair, namely Robo Chair. The system is used to solve the problems. They are - The user head may be out of the image view, or only the profile face is in the captured image, the face colour is user dependent, and may change dramatically in varying illumination conditions, the user may have different facial appearances, such as mustache and glasses, and the background may be cluttered when an Intelligent Wheelchair move in the real world. Hyunduk Kim, Sang Heon Lee, Myoung Kyu Sohn and Dong Ju Kim [2] present a novel approach for head pose estimation in gray level images. The two techniques were employed in this research project. The method of Random Forests was employed for dealing with the large set of training data. In the field of computer vision, this is known as a state of art classification. For the changing in the illumination conditions that is outdoor environmental conditions, a Binary Pattern Run Length matrix is very useful. This matrix is combination of Binary Pattern and a Run Length matrix. The binary pattern was calculated by randomly selected operator. M. Davy and R. Deepa [3] present Head Movement System using Accelerometer Sensor. For detecting the head movements of the users, the system includes the accelerometer sensors.