• Journal of the Ergonomics Society of Korea
• /
• v.31 no.4
• /
• pp.567-575
• /
• 2012

Objective: The aim of this study is to get an optimal mental model by investigating user's natural behavior for controlling smart TV by mid-air gestures and to identify which factor is most important for controlling behavior. Background: A lot of TV companies are trying to find simple controlling method for complex smart TV. Although plenty of gesture studies proposing they could get possible alternatives to resolve this pain-point, however, there is no fitted gesture work for smart TV market. So it is needed to find optimal gestures for it. Method: (1) Eliciting core control scene by in-house study. (2) Observe and analyse 20 users' natural behavior as types of hand-held devices and control scene. We also made taxonomies for gestures. Results: Users' are trying to do more manipulative gestures than symbolic gestures when they try to continuous control. Conclusion: The most natural way to control smart TV on the remote with gestures is give user a mental model grabbing and manipulating virtual objects in the mid-air. Application: The results of this work might help to make gesture interaction guidelines for smart TV.

• Science of Emotion and Sensibility
• /
• v.14 no.4
• /
• pp.627-636
• /
• 2011

The purpose of this study is to develop the multi-modal interaction system. This system provides realistic and an immersive experience through multi-modal interaction. The system recognizes user behavior, intention, and attention, which overcomes the limitations of uni-modal interaction. The multi-modal interaction system is based upon gesture interaction methods, intuitive gesture interaction and attention evaluation technology. The gesture interaction methods were based on the sensors that were selected to analyze the accuracy of the 3-D gesture recognition technology using meta-analysis. The elements of intuitive gesture interaction were reflected through the results of experiments. The attention evaluation technology was developed by the physiological signal analysis. This system is divided into 3 modules; a motion cognitive system, an eye gaze detecting system, and a bio-reaction sensing system. The first module is the motion cognitive system which uses the accelerator sensor and flexible sensors to recognize hand and finger movements of the user. The second module is an eye gaze detecting system that detects pupil movements and reactions. The final module consists of a bio-reaction sensing system or attention evaluating system which tracks cardiovascular and skin temperature reactions. This study will be used for the development of realistic digital entertainment technology.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2004.05b
• /
• pp.616-619
• /
• 2004

As interests Un virtual reality being increased, the importance of HCI(Human computer interaction) field using gesture is also increased. However, in the preceding gesture recognition, the requirement of high-cost peripheral equipments limits users right. In this paper we suggest that through using low cost of USB PC-camera users are allowed to have more flexibly and cost down so that it can be adopted much commonly.

• Journal of the Ergonomics Society of Korea
• /
• v.31 no.4
• /
• pp.515-523
• /
• 2012

Objective: The aim of this study is to investigate users' intuitive stereotypes on non-touch gestures and establish the gesture dictionary that can be applied to gesture-based interaction designs. Background: Recently, the interaction based on non-touch gestures is emerging as an alternative for natural interactions between human and systems. However, in order for non-touch gestures to become a universe interaction method, the studies on what kinds of gestures are intuitive and effective should be prerequisite. Method: In this study, as applicable domains of non-touch gestures, four devices(i.e. TV, Audio, Computer, Car Navigation) and sixteen basic operations(i.e. power on/off, previous/next page, volume up/down, list up/down, zoom in/out, play, cancel, delete, search, mute, save) were drawn from both focus group interview and survey. Then, a user participatory design was performed. The participants were requested to design three gestures suitable to each operation in the devices, and they evaluated intuitiveness, memorability, convenience, and satisfaction of their derived gestures. Through the participatory design, agreement scores, frequencies and planning times of each distinguished gesture were measured. Results: The derived gestures were not different in terms of four devices. However, diverse but common gestures were derived in terms of kinds of operations. In special, manipulative gestures were suitable for all kinds of operations. On the contrary, semantic or descriptive gestures were proper to one-shot operations like power on/off, play, cancel or search. Conclusion: The touchless gesture dictionary was established by mapping intuitive and valuable gestures onto each operation. Application: The dictionary can be applied to interaction designs based on non-touch gestures. Moreover, it will be used as a basic reference for standardizing non-touch gestures.

• 한국HCI학회:학술대회논문집
• /
• 2009.02a
• /
• pp.696-700
• /
• 2009

In this paper, we present a framework which enables users to interact naturally with hand gestures on a digital table. In general tabletop applications, one gesture is mapped to one function or command. Therefore, users should know these relations, and make predefined gestures as input. In contrast, users can make input gesture without cognitive load in our system. Instead of burdening users, the system possesses knowledge about gesture interaction, and infers proactively users' gestures and intentions. When users make a gesture on the digital surface, the system begins to analyze the gestures and designs the response according to users' intention.

• Journal of Korea Multimedia Society
• /
• v.16 no.6
• /
• pp.720-734
• /
• 2013

In this paper, we suggest an augmented reality authoring tool system that users can easily make augmented reality contents using hand gesture and marker-based interaction methods. The previous augmented reality authoring tools are focused on augmenting a virtual object and to interact with this kind of augmented reality contents, user used the method utilizing marker or sensor. We want to solve this limited interaction method problem by applying marker based interaction method and gesture interaction method using depth sensing camera, Kinect. In this suggested system, user can easily develop simple form of marker based augmented reality contents through interface. Also, not just providing fragmentary contents, this system provides methods that user can actively interact with augmented reality contents. This research provides two interaction methods, one is marker based method using two markers and the other is utilizing marker occlusion. In addition, by recognizing and tracking user's bare hand, this system provides gesture interaction method which can zoom-in, zoom-out, move and rotate object. From heuristic evaluation about authoring tool and compared usability about marker and gesture interaction, this study confirmed a positive result.

• Journal of Institute of Control, Robotics and Systems
• /
• v.10 no.9
• /
• pp.771-778
• /
• 2004

Recently, various applications of robot system become more popular in accordance with rapid development of computer hardware/software, artificial intelligence, and automatic control technology. Formerly robots mainly have been used in industrial field, however, nowadays it is said that the robot will do an important role in the home service application. To make the robot more useful, we require further researches on implementation of natural communication method between the human and the robot system, and autonomous behavior generation. The gesture recognition technique is one of the most convenient methods for natural human-robot interaction, so it is to be solved for implementation of intelligent robot system. In this paper, we describe the state-of-the-art of advanced gesture recognition technologies for intelligent robots according to three methods; sensor based method, feature based method, appearance based method, and 3D model based method. And we also discuss some problems and real applications in the research field.

• 한국HCI학회:학술대회논문집
• /
• 2006.02a
• /
• pp.684-691
• /
• 2006

As many functionalities such as cameras and MP3 players are converged to mobile phones, more intuitive and interesting interaction methods are essential. In this paper, we present applications and their enabling technologies for gesture interactive cell phones. They employ gesture recognition and real-time shake detection algorithm for supporting motion-based user interface and entertainment applications respectively. The gesture recognition algorithm classifies users' movement into one of predefined gestures by modeling basic components of acceleration signals and their relationships. The recognition performance is further enhanced by discriminating frequently confusing classes with support vector machines. The shake detection algorithm detects in real time the exact motion moment when the phone is shaken significantly by utilizing variance and mean of acceleration signals. The gesture interaction algorithms show reliable performance for commercialization; with 100 novice users, the average recognition rate was 96.9% on 11 gestures (digits 1-9, O, X) and users' movements were detected in real time. We have applied the motion understanding technologies to Samsung cell phones in Korean, American, Chinese and European markets since May 2005.

• Journal of Institute of Control, Robotics and Systems
• /
• v.18 no.4
• /
• pp.328-336
• /
• 2012

In this paper, we propose a robust fingertip extraction and extended Continuously Adaptive Mean Shift (CAMSHIFT) based robust hand gesture recognition for natural human-like HRI (Human-Robot Interaction). Firstly, for efficient and rapid hand detection, the hand candidate regions are segmented by the combination with robust $YC_bC_r$ skin color model and haar-like features based adaboost. Using the extracted hand candidate regions, we estimate the palm region and fingertip position from distance transformation based voting and geometrical feature of hands. From the hand orientation and palm center position, we find the optimal fingertip position and its orientation. Then using extended CAMSHIFT, we reliably track the 2D hand gesture trajectory with extracted fingertip. Finally, we applied the conditional density propagation (CONDENSATION) to recognize the pre-defined temporal motion trajectories. Experimental results show that the proposed algorithm not only rapidly extracts the hand region with accurately extracted fingertip and its angle but also robustly tracks the hand under different illumination, size and rotation conditions. Using these results, we successfully recognize the multiple hand gestures.

• Korean Journal of Computational Design and Engineering
• /
• v.21 no.1
• /
• pp.20-30
• /
• 2016

Recently immersive virtual reality (VR) becomes popular due to the advanced development of I/O interfaces and related SWs for effectively constructing VR environments. In particular, natural and intuitive manipulation of 3D virtual objects is still considered as one of the most important user interaction issues. This paper presents a comparative study on the manipulation and interaction of 3D virtual objects using different interfaces and interactions in three VR environments. The comparative study includes both quantitative and qualitative aspects. Three different experimental setups are 1) typical desktop-based VR using mouse and keyboard, 2) hand gesture-supported desktop VR using a Leap Motion sensor, and 3) immersive VR by wearing an HMD with hand gesture interaction using a Leap Motion sensor. In the desktop VR with hand gestures, the Leap Motion sensor is put on the desk. On the other hand, in the immersive VR, the sensor is mounted on the HMD so that the user can manipulate virtual objects in the front of the HMD. For the quantitative analysis, a task completion time and success rate were measured. Experimental tasks require complex 3D transformation such as simultaneous 3D translation and 3D rotation. For the qualitative analysis, various factors relating to user experience such as ease of use, natural interaction, and stressfulness were evaluated. The qualitative and quantitative analyses show that the immersive VR with the natural hand gesture provides more intuitive and natural interactions, supports fast and effective performance on task completion, but causes stressful condition.