Aiming at the use of hand gestures for human–computer interaction, this paper presents a real-time approach to the spotting, representation, and recognition of hand gestures from a video stream. The approach exploits multiple cues including skin color, hand motion, and shape. Skin color analysis and coarse image motion detection are joined to perform reliable hand gesture spotting. At a higher ...

The recognition of pen gestures for map-based navigation and annotation is a difficult problem. Especially if users are unconstrained in the gesture repertoires that they can use. This paper reports on a study to develop a taxonomy of pen-gesture shapes in the context of multimodal crisis management applications. A human-factors experiment was conducted for acquiring domain-specific data. A hie...

In this paper, a gesture recognition system based on single tri-axis accelerometer mounted on a cell phone is proposed. We present a novel human computer interaction for cell phone through recognizing seventeen complex gestures. A new feature fusion method for gesture recognition based on time-domain and frequency-domain is proposed. First of all, we extract the time-domain features from accele...

In this paper, we present a computational investigation into the compositionality of iconic gestures by trying to learn a motor grammar. We propose a grammar formalism that learns (1) the salient, invariant features of single movement segments (motor primitives) and (2) the hierarchical organization of these segments in complex gesturing. The formalism is applied to a dataset of natural iconic ...

This paper addresses the issue of how linguistic feedback expressions and head gestures relate to each other. The data are a collection of eight video-recorded Danish map-task dialogues annotated with phonetic and prosodic information. We focus on the analysis of the listeners’ head movements and face expressions and on how they relate to feedback expressions in their different prosodic realisa...

In this paper, we introduced a novel and simple methods of extracting the general features of the hand gestures from surface EMG signal patterns: Hand Extension (H.E), Hand Grasp(H.G),Wrist Extension(W.E),Wrist Flexion(W.F)Pinch(P),Thumb Flexion (T.F). Hand gesture EMG signal classification is demonstrated as a method for prosthesis applications. Recorded electrode signals from the Abductor Pol...

Interest point approaches that extract local features from images are commonly used in human action recognition field. In this paper, a comparison study is performed in which different interest point approaches are used. Each approach is discussed with its advantages and drawbacks. Common keypoints extractor like scale invariant features transform (SIFT), speeded up robust features (SURF), etc....

In this study, the robot arm control, computer vision, and deep learning technologies are combined to realize an automatic control program. There three functional modules in program, i.e., hand gesture recognition module, communication module. The module records user’s images recognize gestures’ features using YOLOv4 algorithm. results transmitted by Finally, received commands analyzed executed...

Almost all consumer electronic equipment today uses remote controls for user interfaces. However, the variety of physical shapes and functional commands that each remote control features also raises numerous problems: the difficulties in locating the required remote control, the confusion with the button layout, the replacement issue and so on. The consumer electronics control system using hand...

In recent years, research in novel types of human-computer interaction, for example multi-touch or tangible interfaces, has increased considerably. Although a large number of innovative applications have already been written based on these new input methods, they often have significant deficiencies from a developer’s point of view. Aspects such as configurability, portability and code reuse hav...