• The Journal of Korea Robotics Society
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• v.17 no.3
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• pp.334-338
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• 2022

In visual simultaneous localization and mapping (vSLAM), the correct recognition of a place benefits in relocalization and improved map accuracy. However, its performance is significantly affected by the environmental conditions such as variation in light, viewpoints, seasons, and presence of dynamic objects. This research addresses the problem of feature occlusion caused by interference of dynamic objects leading to the poor performance of visual place recognition algorithm. To overcome the aforementioned problem, this research analyzes the role of scene semantics in correct detection of a place in challenging environments and presents a semantics aided visual place recognition method. Semantics being invariant to viewpoint changes and dynamic environment can improve the overall performance of the place matching method. The proposed method is evaluated on the two benchmark datasets with dynamic environment and seasonal changes. Experimental results show the improved performance of the visual place recognition method for vSLAM.

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.431-436
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• 1989

A rule-based recognition system for Korean spoken place names using anti-formants which is analyzed by ARMA model is presented. The recognition system is composed of three parts; the extraction, the recognition and the recognition support. As a result of experiment, the recognition rates of city place names was 90.9%.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.19-21
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• 2004

In many cases, human's visual recognition depends on contextual information. We need to use effective feature information for performing vigorous place recognition to illumination, noise, etc. In the existing cases that use edge and color, etc., visual recognition doesn't cope effectively with real environment. To solve this problem, using natural marker, we improve the efficiency of place recognition.

• The Journal of Korea Robotics Society
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• v.6 no.3
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• pp.247-254
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• 2011

This paper presents a method of sonar grid map matching for topological place recognition. The proposed method provides an effective rotation invariant grid map matching method. A template grid map is firstly extracted for reliable grid map matching by filtering noisy data in local grid map. Using the template grid map, the rotation invariant grid map matching is performed by Ring Projection Transformation. The rotation invariant grid map matching selects candidate locations which are regarded as representative point for each node. Then, the topological place recognition is achieved by calculating matching probability based on the candidate location. The matching probability is acquired by using both rotation invariant grid map matching and the matching of distance and angle vectors. The proposed method can provide a successful matching even under rotation changes between grid maps. Moreover, the matching probability gives a reliable result for topological place recognition. The performance of the proposed method is verified by experimental results in a real home environment.

• Journal of Broadcast Engineering
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• v.21 no.4
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• pp.569-577
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• 2016

Place recognition for LBS (Location Based Service) has been one of the important techniques for user-oriented service. FLANN (Fast Library for performing Approximate Nearest Neighbor) of place recognition with image features is fast, but it is affected much by environmental condition such as occlusions. This paper presents a place recognition method using quad vocabulary tree with SURF (Speeded Up Robust Features). In learning stage, an image is represented with spatial pyramid of three levels and vocabulary trees of their sub-regions are constructed. Query image is matched with the learned vocabulary trees in each level. The proposed method measures homography error of the matched features. By considering the number of inliers in sub-region, we can improve place recognition performance.

• Journal of KIISE:Computing Practices and Letters
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• v.14 no.5
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• pp.477-481
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• 2008

Place recognition is necessary for a mobile user to be provided with place-dependent information. This paper proposes real-time video based place recognition system that identifies users' current place while moving in the building. As for the feature extraction of a scene, there have been existing methods based on global feature analysis that has drawback of sensitive-ness for the case of partial occlusion and noises. There have also been local feature based methods that usually attempted object recognition which seemed hard to be applied in real-time system because of high computational cost. On the other hand, researches using statistical methods such as HMM(hidden Markov models) or bayesian networks have been used to derive place recognition result from the feature data. The former is, however, not practical because it requires huge amounts of efforts to gather the training data while the latter usually depends on object recognition only. This paper proposes a combined approach of global and local feature analysis for feature extraction to complement both approaches' drawbacks. The proposed method is applied to a mobile information system and shows real-time performance with competitive recognition result.

• The Journal of Korea Robotics Society
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• v.14 no.1
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• pp.8-13
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• 2019

Visual place recognition is widely researched area in robotics, as it is one of the elemental requirements for autonomous navigation, simultaneous localization and mapping for mobile robots. However, place recognition in changing environment is a challenging problem since a same place look different according to the time, weather, and seasons. This paper presents a feature extraction method using a deep convolutional auto-encoder to recognize places under severe appearance changes. Given database and query image sequences from different environments, the convolutional auto-encoder is trained to predict the images of the desired environment. The training process is performed by minimizing the loss function between the predicted image and the desired image. After finishing the training process, the encoding part of the structure transforms an input image to a low dimensional latent representation, and it can be used as a condition-invariant feature for recognizing places in changing environment. Experiments were conducted to prove the effective of the proposed method, and the results showed that our method outperformed than existing methods.

• Journal of the Korean Institute of Rural Architecture
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• v.24 no.2
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• pp.1-11
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• 2022

Purpose: The purpose of this study is to analyze image factors of places located in natural and humanistically superior geographical locations. It aims to analyze image recognition and spatiality of scenically historical Sahmyook University, located northeast of Gangneung, through standardization. Method: The analysis method of landscape is composed of data investigation and research, and elements of how students, faculty, and visitors recognize a place's beautiful image will be examined. Result: A phenomenological approach was applied to how the images of beautiful place were set by FGI group meeting, and how such factors affect beautiful place's perception from the user's point of view. When looking at comprehensive ranking of image factors in recognition of beautiful landscapes, factors corresponding to forest landscapes appear at the top rank. In determining factors for its recognition, shared space with natural elements such as water, trees, flowers, etc. has been analyzed to have the biggest influence. Among factors corresponding to urban landscape, 'streets and pedestrian paths' is of medium importance and are recognized for it is artificial structure coexisting with natural elements shared with humans. The image corresponding to 'city area' and 'architecture' was analyzed to have insignificant influence on beautiful places' image recognition for artificial element was prioritized.

• Journal of Arbitration Studies
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• v.18 no.3
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• pp.3-22
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• 2008

The purpose of this article is to make research on the meaning and function of the place of arbitration for, the international commercial arbitration. For this purpose is to analyse regal issue the meaning and function of the place of arbitration on the international commercial arbitration relating to the arbitration law and the recognition and enforcement of foreign arbitral awards. In this Article is dealt with Art. 2 para. 1 of the Korean Arbitration Act(KAA). The KAA corresponds with the connection to the place of arbitration, the internationally prevailing 'the principle of territoriality'. The place of arbitration is therefore great practical relevance, as there is not only the existing legal supplements on the arbitration procedure applies, but also in the state courts rule for the support and control of the tribunal are responsible. In this context, this article first intends the importance of the place of arbitration for determination of the applicable procedural law. Secondly, this article intends the importance of the place of arbitration for the recognition and enforcement of foreign arbitral awards under "the United Nations Convention on the Recognition and Enforcement of Foreign Arbitral Awards(New York Convention)". In conclusion, this article stresses, that the place of arbitration setting under Article 21 para. 1 KAA determine not only the applicable arbitration law, but also the jurisdiction of state courts in lawsuit for repeal of arbitration and qualification as a domestic or foreign arbitration award.

• The Journal of Korea Robotics Society
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• v.1 no.2
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• pp.172-179
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• 2006

In this paper, we present a practical place and object recognition method for guiding visitors in building environments. Recognizing places or objects in real world can be a difficult problem due to motion blur and camera noise. In this work, we present a modeling method based on the bidirectional interaction between places and objects for simultaneous reinforcement for the robust recognition. The unification of visual context including scene context, object context, and temporal context is also. The proposed system has been tested to guide visitors in a large scale building environment (10 topological places, 80 3D objects).