Hand gesture recognition system based in computer vision and machine learning

"Lecture notes in computational vision and biomechanics series, ISSN 2212-9391, vol. 19"Hand gesture recognition is a natural way of human computer interaction and an area of very active research in computer vision and machine learning. This is an area with many different possible applications, giving users a simpler and more natural way to communicate with robots/systems interfaces, without the need for extra devices. So, the primary goal of gesture recognition research applied to Human-Computer Interaction (HCI) is to create systems, which can identify specific human gestures and use them to convey information or controlling devices. For that, vision-based hand gesture interfaces require fast and extremely robust hand detection, and gesture recognition in real time. This paper presents a solution, generic enough, with the help of machine learning algorithms, allowing its application in a wide range of human-computer interfaces, for real-time gesture recognition. Experiments carried out showed that the system was able to achieve an accuracy of 99.4% in terms of hand posture recognition and an average accuracy of 93.72% in terms of dynamic gesture recognition. To validate the proposed framework, two applications were implemented. The first one is a real-time system able to help a robotic soccer referee judge a game in real time. The prototype combines a vision-based hand gesture recognition system with a formal language definition, the Referee CommLang, into what is called the Referee Command Language Interface System (ReCLIS). The second one is a real-time system able to interpret the Portuguese Sign Language. Sign languages are not standard and universal and the grammars differ from country to country. Although the implemented prototype was only trained to recognize the vowels, it is easily extended to recognize the rest of the alphabet, being a solid foundation for the development of any vision-based sign language recognition user interface system.(undefined

An initial evaluation of MathPad(2): A tool for creating dynamic mathematical illustrations

MathPad(2) is a pen-based application prototype for creating mathematical sketches. Using a modeless gestural interface, it lets users make dynamic illustrations by associating handwritten mathematics with free-form drawings and provides a set of tools for graphing and evaluating mathematical expressions and solving equations. In this paper, we present the results of an initial evaluation of the MathPad(2) prototype, examining the user interface\u27s intuitiveness and the application\u27s perceived usefulness. Our evaluations are based on both performance and questionnaire results including first attempt gesture performance, interface recall tests, and surveys of user interface satisfaction and perceived usefulness. The results of our evaluation suggest that, although some test subjects had difficulty with our mathematical expression recognizer, they found the interface, in general, intuitive and easy to remember. More importantly, these results suggest the prototype has the potential to assist beginning physics and mathematics students in problem solving and understanding scientific concepts. (c) 2007 Elsevier Ltd. All rights reserved

Investigating User Experience Using Gesture-based and Immersive-based Interfaces on Animation Learners

Creating animation is a very exciting activity. However, the long and laborious process can be extremely challenging. Keyframe animation is a complex technique that takes a long time to complete, as the procedure involves changing the poses of characters through modifying the time and space of an action, called frame-by-frame animation. This involves the laborious, repetitive process of constantly reviewing results of the animation in order to make sure the movement-timing is accurate. A new approach to animation is required in order to provide a more intuitive animating experience. With the evolution of interaction design and the Natural User Interface (NUI) becoming widespread in recent years, a NUI-based animation system is expected to allow better usability and efficiency that would benefit animation. This thesis investigates the effectiveness of gesture-based and immersive-based interfaces as part of animation systems. A practice-based element of this research is a prototype of the hand gesture interface, which was created based on experiences from reflective practices. An experimental design is employed to investigate the usability and efficiency of gesture-based and immersive-based interfaces in comparison to the conventional GUI/WIMP interface application. The findings showed that gesture-based and immersive-based interfaces are able to attract animators in terms of the efficiency of the system. However, there was no difference in their preference for usability with the two interfaces. Most of our participants are pleasant with NUI interfaces and new technologies used in the animation process, but for detailed work and taking control of the application, the conventional GUI/WIMP is preferable. Despite the awkwardness of devising gesture-based and immersive-based interfaces for animation, the concept of the system showed potential for a faster animation process, an enjoyable learning system, and stimulating interest in a kinaesthetic learning experience

Assessing the effectiveness of direct gesture interaction for a safety critical maritime application

Multi-touch interaction, in particular multi-touch gesture interaction, is widely believed to give a more natural interaction style. We investigated the utility of multi-touch interaction in the safety critical domain of maritime dynamic positioning (DP) vessels. We conducted initial paper prototyping with domain experts to gain an insight into natural gestures; we then conducted observational studies aboard a DP vessel during operational duties and two rounds of formal evaluation of prototypes - the second on a motion platform ship simulator. Despite following a careful user-centred design process, the final results show that traditional touch-screen button and menu interaction was quicker and less erroneous than gestures. Furthermore, the moving environment accentuated this difference and we observed initial use problems and handedness asymmetries on some multi-touch gestures. On the positive side, our results showed that users were able to suspend gestural interaction more naturally, thus improving situational awareness

Gesture Based Interface for Asynchronous Video Communication for Deaf People in South Africa

The preferred method of communication amongst Deaf people is that of sign language. There are problems with the video quality when using the real-time video communication available on mobile phones. The alternative is to use text-based communication on mobile phones, however findings from other research studies show that Deaf people prefer using sign language to communicate with each other rather than text. This dissertation looks at implementing a gesture-based interface for an asynchronous video communication for Deaf people. The gesture interface was implemented on a store and forward video architecture since this preserves the video quality even when there is low bandwidth. In this dissertation three gesture-based video communication prototypes were designed and implemented using a user centred design approach. These prototypes were implemented on both the computer and mobile devices. The first prototype was computer based and the evaluation of this prototype showed that the gesture based interface improved the usability of sign language video communication. The second prototype is set up on the mobile device and it was tested on several mobile devices but the device limitation made it impossible to support all the features needed in the video communication. The different problems experienced on the dissimilar devices made the task of implementing the prototypes on the mobile platform challenging. The prototype was revised several times before it was tested on a different mobile phone. The final prototype used both the mobile phone and the computer. The computer served to simulate a mobile device with greater processing power. This approach simulated a more powerful future mobile device capable of running the gesture-based interface. The computer was used for video processing but to the user it was as if the whole system was running on the mobile phone. The evaluation process was conducted with ten Deaf users in order to determine the efficiency and usability of the prototype. The results showed that the majority of the users were satisfied with the quality of the video communication. The evaluation also revealed usability problems but the benefits of communicating in sign language outweighed the usability difficulties. Furthermore the users were more interested in the video communication on the mobile devices than on the computer as this was a much more familiar technology and offered the convenience of mobility

Wearable Capacitive-based Wrist-worn Gesture Sensing System

Gesture control plays an increasingly significant role in modern human-machine interactions. This paper presents an innovative method of gesture recognition using flexible capacitive pressure sensor attached on user’s wrist towards computer vision and connecting senses on fingers. The method is based on the pressure variations around the wrist when the gesture changes. Flexible and ultrathin capacitive pressure sensors are deployed to capture the pressure variations. The embedding of sensors on a flexible substrate and obtain the relevant capacitance require a reliable approach based on a microcontroller to measure a small change of capacitive sensor. This paper is addressing these challenges, collect and process the measured capacitance values through a developed programming on LabVIEW to reconstruct the gesture on computer. Compared to the conventional approaches, the wrist-worn sensing method offerings a low-cost, lightweight and wearable prototype on the user’s body. The experimental result shows that the potentiality and benefits of this approach and confirms that accuracy and number of recognizable gestures can be improved by increasing number of sensor