# Gesture-Based User Interface for Vehicle On-Board System: A Questionnaire and Research Approach
## 3 Proposed Approach of Gesture-Based Interaction Interface
### Gesture Recognition  
Two types of hand gestures are defined in the scientific literature, namely: static and dynamic [37]. Static gestures are sometimes called as postures while dynamic-as hand motions. A Static gesture denotes a specific orientation and position of hand in the space. The gesture lasts a specific period of time without any movement associated with it. A thumb up as an OK symbol is a good example here. A dynamic gesture requires a specific movement performed during a predefined time window. A hand moving forward in the air as if pressing a button or waving of hand are examples of dynamic gestures.  
Figure 3 presents a set of established gestures we employed in our investigation. A gesture number one can be described as a movement of the hand, facing the sensor, to the left and immediately back to the starting position. Similar is the case with gesture number two, but the movement is to the right. Gestures number 3 and 4 mean respectively: a movement of the hand, facing the sensor, downwards and immediately back to the starting position and a movement of the hand, facing the sensor, upwards and immediately back to the starting position. These four gestures constitute for a typical swipe mechanism.  
The gesture number 5 means: move a hand close to the sensor and move it back in a way that imitates pressing a button. All the first 5 gestures presented in Figure 3 are typical dynamic gestures. The definition of gesture number 6 is: show a clenched hand towards the sensor. This is a static gesture similarly as the last one. The 7 th gesture is defined as presentation of the hand with index and middle finger upwards with others hidden.  
We have chosen for our investigations only those gestures that seems to be easy to perform, are natural, and engage small number of muscles. These are four directional swipe gestures, a push gesture and two static gestures (clenched fist and victory gesture). It must be noticed that many gestures are not well suited for the in-car environment. They require more space to be performed properly or engage too many muscles. The latter is especially important for people with physical limitations. For example, a \"thumb down\" gesture is performed with a closed hand and straightened thumb, but the rotary arm movement is required so that the thumb points down. Other gestures, like \"spread fingers\" might be extremely difficult for people with disabilities. We believe that our selected gestures are the easiest but for sure, in future, the user specific adaptation should be considered.  
Figure 3: A set of gesture included in presented research. (Based on [38]).  
Figure 2: Intel RealSense sr300 sensor [own work based on [[https://us.creative.com/p/web-cameras/blasterx-sen23d](https://us.creative.com/p/web-cameras/blasterx-sen23d)]([https://us.creative.com/p/web-cameras/blasterx-sen23d](https://us.creative.com/p/web-cameras/blasterx-sen23d))].  
Gesture recognition is still an active research activity with many established solutions available for researchers. In our proposal we based the gesture recognition module on libraries provided with the Intel RealSense sr300. The hardware details of this solution has been provided in Section 3.1. The gesture recognition mechanisms are based here on skeletal and blob (silhouette) tracking. The most advanced mode is called \"Full-hand\" and offers tracking of 22 joints of the hand in 3D [38]. This mode requires the highest computational resources but offers the recognition of pre-defined gestures. The second is the \"Extremities mode\" and it offers tracking of 6 points: the hand's top-most, bottom-most, right-most, left-most, center and closest (to the sensor) points [38]. Other modes include \"Cursor\" and \"Blob\". They are reserved for the simplest cases when central position of hand or any object is expected to be tracked.