Gesture recognition (GR) is a field of computer science which plays a vital role in interpreting human gestures with the help of computer vision algorithms. Based on the kind of input data the approach to interpret gestures keeps varying. This technique acts as a Human Machine Interface (HMI) and serves as a bridge for interacting between the system and the machine with ease. This is an improved technology when compared with the traditional text user interface and GUIs (Graphical User Interface) as most of the input in them are given using keyboard and mouse. GR acts as a vibrant tool for the computer to understand the sign and body language of human. Using GR it is possible to perform operations with the help of simple gestures. The quality of the input and the complexity of algorithms play a decisive role in determining the accuracy of the output. In order to recognize the movement of the body, classification has to be done based on the common properties and other features that could be taken into consideration. The challenges faced by GR are the usefulness and accuracy of the gesture recognition software. The noise present in the background also poses a serious challenge to tracking and recognition difficulties especially when occlusion comes into play. The main focus in this field includes emotion recognition from face and hand gesture recognition.

Topics of interest include but are not limited to:

1. Use of image processing in the present scenario
2. Gesture recognition
3. Computer vision
4. Image processing
5. Real time applications of image processing
6. Artificial intelligence
7. Measures to resolve issues in image processing