The use of gesture as a natural interface serves as a motivating force for research in modeling, analyzing and recognition of gestures. In particular, human computer intelligent interaction needs vision-based gesture recognition, which involves many interdisciplinary studies. A survey on recent vision-based gesture recognition approaches is given in this paper. We shall review methods of static...

Wearable computing and Augmented Reality applications call for less obtrusive and more intuitive human computer interfaces than keyboards and mice. One way to realise such interfaces is using gestures, e.g., for pointing in order to replace the mouse. The less obtrusive way of gesture recognition is to use computer vision based methods. This paper presents a computer vision-based gesture interf...

One of the most important techniques in human-robot communication is gesture recognition. If robots can read intentions from human gestures, the communication process will be smoother and more natural. Processing for gesture recognition typically consists of two parts: feature extraction and gesture classification. In most works, these are independently designed and evaluated by their own crite...

Multiple studies (Galati & Brennan, 2014; Hoetjes, Koolen, Goudbeek, Krahmer, & Swerts, 2001; Jacobs & Garnham, 2007) have shown reduction in co-speech gesture across repetition. Reduction can be interpreted in terms of demonstrating automatization of effort (Vajrabhaya & Pederson, 2014). This study specifically investigates a special type of gesture used when speakers are accessing a low-famil...

BACKGROUND Human communication occurs through both verbal and visual/motoric modalities. Simultaneous conversational speech and gesture occurs across all cultures and age groups. When verbal communication is compromised, more of the communicative load can be transferred to the gesture modality. Although people with aphasia produce meaning-laden gestures, the communicative value of these has not...

In this paper, we introduce a hand gesture recognition system to recognize real time gesture in unconstrained environments. The system consists of three modules: real time hand tracking, training gesture and gesture recognition using pseudo two dimension hidden Markov models (P2-DHMMs). We have used a Kalman filter and hand blobs analysis for hand tracking to obtain motion descriptors and hand ...