DESIGNING HAND GESTURE VOCABULARIES FOR NATURAL INTERACTION BY COMBINING PSYCHO-PHYSIOLOGICAL AND RECOGNITION FACTORS (original) (raw)

This work presents an analytical approach to design a gesture vocabulary (GV) using multiobjectives for psycho-physiological and gesture recognition factors. Previous works dealt only with selection of hand gestures vocabularies using rule based or ad-hoc methods. The analytical formulation in our research is a demonstration of the future need defined by previous research. A meta-heuristic approach is taken by decomposing the problem into two sub-problems: (i) finding the subsets of gestures that meet a minimal accuracy requirement, and (ii) matching gestures to commands to maximize the human factors objective. The result is a set of solutions from which a Pareto optimal subset is selected. An example solution from the Pareto set is exhibited using prioritized objectives.

Abstract A global approach to hand gesture vocabulary (GV) design is proposed which includes human as well as technical design factors. The human centered desires (intuitiveness, comfort) of multiple users are implicitly represented through indices obtained from ergonomic studies representing the psycho-physiological aspects of users. The main technical aspect considered is that of machine recognition of gestures. We believe this is the first conceptualization of the optimal hand gesture design problem in analytical form.

Hand gestures to control systems require accurate recognition, high learnability, usability, ergonomic design and comfort. Unfortunately, most gesture interfaces are designed with the technical consideration of recognition accuracy as the central focus. In this research we consider hand gestures that are unencumbered, ie; can be captured with camera vision devices. The selection of a set of hand gestures that consider both recognition accuracy as well as the ease of learning, lack of stress, cognitively natural and ease of implementation ...

The use of gestures to convey information has been an important part of human communication. Hand gestures can be classified into two categories: static and dynamic. The use of hand gestures as a natural interface serves as a motivating force for research on gesture nomenclature, its representations, and recognition techniques. This paper is the summary of the reviews carried out in human computer interaction (HCI) studies and concentrates on different application domains that use hand gestures for efficient interaction. This fact-finding study wishes to provide a progress report on static and dynamic hand gesture recognition (i.e., gesture taxonomies, representations, and recognition techniques) in HCI and to identify future directions. Keywords—Gesture recognition, Human Computer Interaction (HCI), AI, Language Processing. INTRODUCTION With the development of information technology in our society, we can expect that computer systems to a larger extent will be embedded into our env...

Hand gesture based interfaces are a proliferating area for immersive and augmented reality systems due to the rich interaction provided by this type of modality. Even though proper design of such interfaces requires accurate recognition, usability, ergonomic design and comfort. In most of the interfaces being developed the primary focus is on accurate gesture recognition. Formally, an optimal hand gesture vocabulary (GV), can be defined as a set of gesture-command associations, such that the time τ to perform a task is ...

We present a novel and trainable gesture-based system for next-generation intelligent interfaces. The system requires a non-contact depth sensing device such as an RGB-D (color and depth) camera for user input. The camera records the user's static hand pose and palm center dynamic motion trajectory. Both static pose and dynamic trajectory are used independently to provide commands to the interface. The sketches/symbols formed by palm center trajectory is recognized by the Support Vector Machine classifier. Sketch/symbol recognition process is based on a set of geometrical and statistical features. Static hand pose recognizer is incorporated to expand the functionalities of our system. Static hand pose recognizer is used in conjunction with sketch classification algorithm to develop a robust and effective system for natural and intuitive interaction. To evaluate the performance of the system user studies were performed on multiple participants. The efficacy of the presented syste...