A survey of hand gesture dialogue modeling for map navigation <s> INTRODUCTION <s> A small group of hand gestures made during conversation (interactive gestures) seem to function solely to assist the process of dialogue rather than to convey topical information. The rate of interactive gestures was significantly higher when 27 dyads talked in dialogue than in sequential monologues, whereas the rate of other (topical) gestures did not change; this difference supports the theory that interactive gestures are uniquely affected by the requirements of dialogue. A second, microanalytic study tested hypotheses about the specific functions of interactive gestures by examining the responses of the person to whom the gesture was addressed. Predictions were correct for 78 of 88 gestures sampled randomly from a large database. These results support the conclusion that interactive gestures are an important means by which speakers can include their addressees in the conversation. Moreover, these gestures demonstrate the importance of social (dialogic) processes in language use. <s> BIB001 </s> A survey of hand gesture dialogue modeling for map navigation <s> INTRODUCTION <s> Visual hand gestures offer an interesting modality for Human-Computer-Interaction (HCI) applications. Gesture recognition and hand tracking, however, are not trivial tasks and real environments set a lot of challenges to algorithms performing such activities. In this paper, a novel combination of techniques is presented for tracking and recognition of hand gestures in real, cluttered environments. In addition to combining existing techniques, a method for locating a hand and segmenting it from an arm in binary silhouettes and a foreground model for color segmentation is proposed. A single hand is tracked with a single camera and the trajectory information is extracted along with recognition of five different gestures. This information is exploited for replacing the operations of a normal computer mouse. The silhouette of the hand is extracted as a combination of different segmentation methods: An adaptive colour model based segmentation is combined with intensity and chromaticity based background subtraction techniques to achieve robust performance in cluttered scenes. An affine-invariant Fourier-descriptor is derived from the silhouette, which is then classified to a hand shape class with support vector machines (SVM). Gestures are recognized as changes in the hand shape with a finite state machine (FSM). <s> BIB002 </s> A survey of hand gesture dialogue modeling for map navigation <s> INTRODUCTION <s> Hand tracking is an important component in most practical gesture interaction. Due to background variety, illumination changes and aiticulate shape, it's difficult for current conventional vision based methods to obtain accurate results. In this paper, an automatic hand tracking and segmentation method based on depth information is proposed. Hand depth is determined adaptively and then accurate hand region is obtained. In this manner, accurate hand tracking is realized with very low time consumption and regardless of the complex background and various illuminations. Moreover, based on the real-time hand tracking, a robust dynamic gesture recognition strategy is described. Considering the geometric characters, the gestures are classified according to the trajectory fitting and matching with the predefined patterns. Experiments show the effectiveness of the hand tracking and dynamic gesture recognition. Furthermore, a concrete application scenario, gesture controlled map navigation, is implemented with good interaction usability. <s> BIB003 </s> A survey of hand gesture dialogue modeling for map navigation <s> INTRODUCTION <s> Hand gestures and speech constitute one of the most important modalities in human-to-human communication. The investigation of this phenomenon has been the focus of research about multimodal interfaces for speech and hand gesture recognition in human computer interaction(HCI). Computer games, as one of the most popular application areas of HCI, are likely to make use of this technology. Integration of speech and gesture in computer games make game play more enjoyable. This article does not intend to cover exhaustively all the issues related to multimodal interface creation in computer games. We primarily discuss some of the key issues related to multimodal interfaces for speech and hand gesture recognition and present a survey of current approaches to overcome the problems faced in this area. <s> BIB004 </s> A survey of hand gesture dialogue modeling for map navigation <s> INTRODUCTION <s> The hand gesture recognition system is widely used in the development of human-machine interaction. The vision-based hand gesture recognition is achieved by the following steps: preprocessing, feature extraction and classification. The aim of preprocessing stage is to localize the hand region from the image frame. The Laplacian of Gaussian filtering technique along with zero crossing detector is applied on hand gesture images to detect the edges of hand region. This work proposes a novel feature extraction technique, which is based on local histogram feature descriptor (LHFD). The proposed feature is extracted by finding the local histogram of the grayscale gesture image. This technique uses the whole region of the hand to extract the features. The proposed method is invariant to the scaling and illumination. Two standard datasets viz. Massey University gesture dataset (MUGD) and Jochen Triesch static hand posture database are used to evaluate the recognition performance of the proposed technique. The gesture recognition performance of the proposed technique is 99.5%and 95%on Massey University gesture dataset and Triesch dataset respectively, using support vector machine (SVM) classifier. Fourier descriptor along with Convolutional neural network is proposed for continuous frame based hand gesture recognition. Fourier descriptor is used to construct the smooth boundary of each frame of video. CNN is used for classification, the recognition accuracy of the proposed method for dynamic hand gesture recognition is of77:5% <s> BIB005
Hand gesture usually performance during communication between human to human. It can deliver the message from a person to the other such as refuse sales person to approach with shaking the hand left and right. Hand gesture not only work with human to human but also ISSN: 2252-4274 (Print) ISSN: 2252-5459 (Online) human with pets.A well trained dog will follow instruction from the instructor like palm moving up meaning stand, and palm moving down meaning to sit. Different movements and combinations of hand gesture can express a lot of meaningful messages just like sign language, however the complexity of hand gesture is one the difficult tasks to be modeled BIB002 . Hand gesture dialogue BIB001 is the specialized language using hand gesture when interacting with others. Hence, the used of hand gesture dialogue varies depend on different situation. Appropriate design of hand gesture dialogue needed when dealing with different type of interaction such as computer games, map navigation, etc. In this paper, the map navigation interface task being taken because of the large magnitude of scale and the spatial space  . However, this challenge increases the difficulty of interface design. Most of the research concentrates on hand gesture recognition BIB002 BIB005 and hand tracking BIB003 . They ignore the importance of decent hand gesture dialogue can achieve a higher user performance. Hand gesture input would certainly improve the latter role by supplying users with more natural control. Unfortunately, the hand gesture dialogue used to interact with computers in recognition systems have not been designed at all to cooperate BIB004 . To build interfaces for hand gesture recognition in map navigation, the key issue is how to model hand gesture dialogue to achieve maximum benefit. One of the most significant challenges in this area is the modeling of effective hand gesture dialogue that can support map navigation. In the following parts, we will first review related applications of interfaces in map navigation and then discuss the related issues about dialogue modeling.