• Proceedings of the IEEK Conference
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• 2005.11a
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• pp.553-556
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• 2005

We present a vision-based hand gesture recognition system for object manipulation in virtual space. Most conventional hand gesture recognition systems utilize a simpler method for hand detection such as background subtractions with assumed static observation conditions and those methods are not robust against camera motions, illumination changes, and so on. Therefore, we propose a statistical method to recognize and detect hand regions in images using geometrical structures. Also, Our hand tracking system employs multiple cameras to reduce occlusion problems and non-synchronous multiple observations enhance system scalability. Experimental results show the effectiveness of our method.

• Journal of the Korea Institute of Military Science and Technology
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• v.27 no.3
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• pp.375-386
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• 2024

Autonomous weapon systems act according to artificial intelligence-based judgement based on recognition through various sensors. Test and evaluation for various scenarios is required depending on the characteristics that artificial intelligence-based judgement is made. As a part of this approach, this paper proposed a LiDAR point cloud augmentation method for mixed-reality based test and evaluation. The augmentation process is achieved by mixing real and virtual LiDAR signals based on the virtual LiDAR synchronized with the pose of the autonomous weapon system. For realistic augmentation of test and evaluation purposes, appropriate intensity values were inserted when generating a point cloud of a virtual object and its validity was verified. In addition, when mixing the generated point cloud of the virtual object with the real point cloud, the proposed method enhances realism by considering the occlusion phenomenon caused by the insertion of the virtual object.

• Journal of Drive and Control
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• v.19 no.3
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• pp.9-15
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• 2022

This paper proposes a method for constructing and verifying datasets used in deep learning technology, to prevent safety accidents in automated construction machinery or autonomous vehicles. Although open datasets for developing image recognition technologies are challenging to meet requirements desired by users, this study proposes the interface of virtual simulators to facilitate the creation of training datasets desired by users. The pixel-level training image dataset was verified by creating scenarios, including various road types and objects in a virtual environment. Detecting an object from an image may interfere with the accurate path determination due to occlusion areas covered by another object. Thus, we construct a database, for developing an occlusion area detection algorithm in a virtual environment. Additionally, we present the possibility of its use as a deep learning dataset to calculate a grid map, that enables path search considering occlusion areas. Custom datasets are built using the RDBMS system.

• Journal of information and communication convergence engineering
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• v.8 no.4
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• pp.411-415
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• 2010

Conventional Augmented Reality has used data gloves or markers for smooth interaction between objects and background. This causes inconvenience of use and lower immersion. To build up immersion in Augmented Reality, additional input devices must be removed. For this purpose, accurate recognition of space coordinates is needed even with no attachment of markers. This paper proposes a method to create virtual space coordinates for interaction without wearing additional input devices so as to improve immersion in Augmented Reality. The acquired image was projected to 2D space and vanishing lines were extracted to calculate the virtual space coordinates. Then the sizes of the inserted objects were varied in accordance with the size of the virtual coordinates area based on the image projected onto the 2D coordinates. This resulted in improved immersion. This method can increase the efficiency of object creation by excluding the use of a 3D modeler for creation of 3D objects.

• Convergence Security Journal
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• v.22 no.5
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• pp.3-9
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• 2022

Recently, in order to build a cyber physical system(CPS) that is a technology related to the 4th industry, the construction of the virtual control system for physical model and control circuit simulation is increasingly required in various industries. It takes a lot of time and money to convert documents that are not electronically documented through direct input. For this, it is very important to digitize a large number of drawings that have already been printed through object recognition using artificial intelligence. In this paper, in order to accurately recognize objects in drawings and to utilize them in various applications, a recognition technique using artificial intelligence by analyzing the characteristics of objects in drawing was proposed. In order to improve the performance of object recognition, each object was recognized and then an intermediate file storing the information was created. And the recognition rate of the next recognition target was improved by deleting the recognition result from the drawing. In addition, the recognition result was stored as a standardized format document so that it could be utilized in various fields of the control system. The excellent performance of the technique proposed in this paper was confirmed through the experiments.

• 한국HCI학회:학술대회논문집
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• 2006.02b
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• pp.633-638
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• 2006

We investigated the importance and efficiency of active and passive exploration on the recognition of objects in a variety of virtual environments (VEs). In this study, 54 participants (19 males and 35 females) were randomly allocated into one of two navigation conditions (active and passive navigation). The 3D visual display was presented through HMD and participants used joysticks to navigate VEs. The VEs consisted of exploring four rooms (library, office, lounge, and conference room), each of which had 15 objects. 'Active navigation' was performed by allowing participants to self-pace and control their own navigation within a predetermined time limitation for each room. 'Passive navigation' was conducted by forced navigation of the four rooms in random order. Total navigation duration and objects for both navigations were identical. After navigating VEs, participants were asked to recognize the objects that had been in the four rooms. Recognition for objects was measured by response time and the percentage of correct, false, hit, and miss responses. Those in the active navigation condition had a significantly higher percentage of hit responses (t (52) = 4.000 p < 0.01), and a significantly lower percentage of miss responses (t (52) = -3.763, p < 0.01) in object recognition than those in the passive condition. These results suggest that active navigation plays an important role in spatial cognition as well as providing a better explanation about the efficiency of learning in a 3D-based program.

• Journal of Information Processing Systems
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• v.13 no.4
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• pp.876-892
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• 2017

A virtual reality is a virtual space constructed by a computer that provides users the opportunity to indirectly experience a situation they have not experienced in real life through the realization of information for virtual environments. Various studies have been conducted to realize virtual reality, in which the user interface is a major factor in maximizing the sense of immersion and usability. However, most existing methods have disadvantages, such as costliness or being limited to the physical activity of the user due to the use of special devices attached to the user's body. This paper proposes a new type of interface that enables the user to apply their intentions and actions to the virtual space directly without special devices, and test content is introduced using the new system. Users can interact with the virtual space by throwing an object in the space; to do this, moving object detectors are produced using infrared sensors. In addition, the users can control the virtual space with their own postures. The method can heighten interest and concentration, increasing the sense of reality and immersion and maximizing user's physical experiences.

• Journal of Drive and Control
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• v.18 no.4
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• pp.9-18
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• 2021

This study proposes a method for creating learning datasets to recognize obstacles using deep learning algorithms in automated construction machinery or an autonomous vehicle. Recently, many researchers and engineers have developed various recognition algorithms based on deep learning following an increase in computing power. In particular, the image classification technology and image segmentation technology represent deep learning recognition algorithms. They are used to identify obstacles that interfere with the driving situation of an autonomous vehicle. Therefore, various organizations and companies have started distributing open datasets, but there is a remote possibility that they will perfectly match the user's desired environment. In this study, we created an interface of the virtual simulator such that users can easily create their desired training dataset. In addition, the customized dataset was further advanced by using the RDBMS system, and the recognition rate was improved.

• ETRI Journal
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• v.34 no.3
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• pp.466-469
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• 2012

In this letter, we propose a dual autostereoscopic display platform employing a natural interaction method, which will be useful for sharing visual data with users. To provide 3D visualization of a model to users who collaborate with each other, a beamsplitter is used with a pair of autostereoscopic displays, providing a visual illusion of a floating 3D image. To interact with the virtual object, we track the user's hands with a depth camera. The gesture recognition technique we use operates without any initialization process, such as specific poses or gestures, and supports several commands to control virtual objects by gesture recognition. Experiment results show that our system performs well in visualizing 3D models in real-time and handling them under unconstrained conditions, such as complicated backgrounds or a user wearing short sleeves.

• Journal of Korea Game Society
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• v.20 no.2
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• pp.183-192
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• 2020

Due to the problem of matching between virtual world space and real-world space, the reality of augmented reality content is rather low. There are many reasons for this result, firstly virtual object is rendered without considering relation between real-world space and virtual world space. Secondly, virtual objects rely too much on the marker to reduce reality. We propose two schemes to improve the reality of augmented reality, one is people occlusion, the other is to reduce the dependence of virtual objects on the marker.