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Hand Gesture

PostPosted: Tue Dec 24, 2013 8:19 am
by Prasanth
This paper presents a new approach for Human Machine Interaction (HMI) by merely showing hand gestures in front of a camera. With the help of this technique one can pose a hand gesture in the vision range of a robot and corresponding to this notation, desired operation is performed by the machine. Simple video camera is used for computer vision, which helps in monitoring gesture presentation. This approach consists of four modules: (a) A real time hand gesture formation monitor and gesture capture, (b) feature extraction, (c) Pattern matching for gesture recognition, (d) Command determination corresponding to shown gesture and performing operation by the machine. Real-time hand tracking technique is used for object detection in the range of vision. If a hand gesture is shown for one second, the camera captures the gesture. Object of interest is extracted from the background and the portion of hand, representing the gesture, is cropped out using the statistical property of hand. Extracted hand gesture is matched with the stored database of hand gestures using pattern matching. Corresponding to the matched gesture, action is performed by the machine. This system can be used for controlling robots such as movement of robots, operations of robots etc...


Interpretation of human gestures by a computer is used for human-machine interaction in the area of computer vision. The main purpose of gesture recognition research is to identify a particular human gesture and convey information to the user pertaining to individual gesture. From the corpus of gestures, specific gesture of interest can be identified, and on the basis of that, specific command for execution of action can be given to the machine. Overall aim is to make the computer to understand human body language, thereby bridging the gap between machine and human. Hand gesture recognition can be used to enhance human– computer interaction without depending on traditional input devices such as keyboard and mouse. Hand gestures are extensively used for telerobotic control and applications. Robotic systems can be controlled naturally and intuitively with such telerobotic communication. A prominent benefit of such a system is that it presents a natural way to send geometrical information to the robot such as: left, right, etc. Robotic hand can be controlled remotely by hand gestures. Research is being carried out in this area for a long time. Several approaches have been developed for sensing hand movements and corresponding by controlling robotic hand.

Glove based technique is well-known means of recognizing hand gestures. It utilizes sensor-detached mechanical glove devices that directly measure hand and/or arm joint angles and spatial position. Although glove-based gestural interfaces give more precision, it limits freedom as it requires users to wear cumbersome patch of devices. Jae-Ho Shin used entropy analysis to extract hand region in complex background for hand gesture recognition system. Robot controlling is done by Fusion of Hand Positioning and Arm Gestures using data glove. Although it gives more precision, it limits freedom due to necessity of wearing gloves. For capturing hand gestures correctly, proper light and camera angle are required. The problem of visual hand recognition and tracking is quite challenging. Many early approaches used position markers or colored bands to make the problem of hand recognition easier, but due to their inconvenience, they cannot be considered as a natural interface for the robot control. We have proposed a fast as well as automatic hand gesture detection and recognition system. This approach of gesture identification On the basis of recognized hand gesture can be used in any robotic system or machines with a number of specific commands suitable to that system.


Gesture recognition is a topic in computer science and language technology with the goal of interpreting human gestures via mathematical algorithms. Gestures can originate from any bodily motion or state but commonly originate from the face or hand. Current focuses in the field include emotion recognition from the face and hand gesture recognition. Many approaches have been made using cameras and computer vision algorithms to interpret sign language. However, the identification and recognition of posture, gait, and human behaviours is also the subject of gesture recognition techniques.[1]
huGesture recognition can be seen as a way for computers to begin to understand man body language, thus building a richer bridge between machines and humans than primitive text user interfaces or even GUIs (graphical user interfaces), which still limit the majority of input to keyboard and mouse.
Gesture recognition enables humans to interface with the machine (HMI) and interact naturally without any mechanical devices. Using the concept of gesture recognition, it is possible to point a finger at the computer screen so that the cursor will move accordingly. This could potentially make conventional input devices such as mouse, keyboards and even touch-screens redundant.

Gesture recognition can be conducted with techniques from computer vision and image processing.

A gesture recognition system could be used in any of the following areas:

• Man-machine interface: using hand gestures to control the computer mouse and/or keyboard functions.
• 3D animation: Rapid and simple conversion of hand movements into 3D computer space for the purposes of computer animation.
• Visualization: Just as objects can be visually examined by rotating them with the hand, so it would be advantageous if virtual 3D objects (displayed on the computer screen) could be manipulated by rotating the hand in space
• Computer games: Using the hand to interact with computer games would be more natural for many applications.
• Control of mechanical systems (such as robotics): Using the hand to remotely control a manipulator.

There are many challenges associated with the accuracy and usefulness of gesture recognition software. For image-based gesture recognition there are limitations on the equipment used and image noise. Images or video may not be under consistent lighting, or in the same location. Items in the background or distinct features of the users may make recognition more difficult.

Re: Hand Gesture

PostPosted: Mon Jan 27, 2014 8:01 pm
by afreen79
can you give us the ppt of this topic..!

Re: Hand Gesture

PostPosted: Tue Mar 25, 2014 4:19 pm
by internet
afreen79 wrote:can you give us the ppt of this topic..!

i too, would like a ppt for the same.thank you