• Journal of Sensor Science and Technology
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• v.33 no.2
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• pp.98-104
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• 2024

This study proposes a method to overcome the limited detection range of short-baseline stereo cameras (SBSCs). The proposed method includes two steps: (1) predicting an unscaled initial depth using monocular depth estimation (MDE) and (2) adjusting the unscaled initial depth by a scale factor. The scale factor is computed by triangulating the sparse visual keypoints extracted from the left and right images of the SBSC. The proposed method allows the use of any pre-trained MDE model without the need for additional training or data collection, making it efficient even when considering the computational constraints of small platforms. Using an open dataset, the performance of the proposed method was demonstrated by comparing it with other conventional stereo-based depth estimation methods.

• Journal of KIISE:Databases
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• v.35 no.5
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• pp.379-390
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• 2008

Due to the increase of the amount of image data, the demand for searching similar images is continuously increasing. Therefore, many researches about the content-based image retrieval (CBIR) are conducted to search similar images effectively. In CBIR, it uses image contents such as color, shape, and texture for more effective retrieval. However, when we apply CBIR to satellite images which are complex and pose the difficulty in using color information, we can have trouble to get a good retrieval result. Since it is difficult to use color information of satellite images, we need image segmentation to use shape information by separating the shape of an object in a satellite image. However, because satellite images are complex, image segmentation is hard and poor image segmentation results in poor retrieval results. In this paper, we propose a new approach to search similar images without image segmentation for satellite images. To do a similarity search without image segmentation, we define a similarity of an image by considering SIFT keypoint descriptors which doesn't require image segmentation. Experimental results show that the proposed approach more effectively searches similar satellite images which are complex and pose the difficulty in using color information.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.27 no.3
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• pp.393-400
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• 2009

Recently demand for the 3D modeling technology to reconstruct real world is getting increasing. However, existing geospatial data are mainly based on the 2D space. In addition, most of the geospatial data provide geometric information only. In consequence, there are limits in various applications to utilize information from those data and to reconstruct the real world in 3D space. Therefore, it is required to develop efficient 3D mapping methodology and data for- mat to establish geospatial database. Especially digital elevation model(DEM) is one of the essential geospatial data, however, DEM provides only spatially distributed 3D coordinates of the natural and artificial surfaces. Moreover, most of DEMs are generated without considering terrain properties such as surface roughness, terrain type, spatial resolution, feature and so on. This paper suggests adaptive and flexible geospatial data format that has possibility to include various information such as terrain characteristics, multiple resolutions, interpolation methods, break line information, model keypoints, and other physical property. The study area was categorized into mountainous area, gently rolling area, and flat area by taking the terrain characteristics into account with respect to terrain roughness. Different resolutions and interpolation methods were applied to each area. Finally, a 3D digital map derived from aerial photographs was integrated with the geospatial data and visualized.

• Journal of Internet of Things and Convergence
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• v.10 no.2
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• pp.1-15
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• 2024

The construction of smart communities is a new method and important measure to ensure the security of residential areas. In order to solve the problem of low accuracy in face recognition caused by distorting facial features due to monitoring camera angles and other external factors, this paper proposes the following optimization strategies in designing a face recognition network: firstly, a global graph convolution module is designed to encode facial features as graph nodes, and a multi-scale feature enhancement residual module is designed to extract facial keypoint features in conjunction with the global graph convolution module. Secondly, after obtaining facial keypoints, they are constructed as a directed graph structure, and graph attention mechanisms are used to enhance the representation power of graph features. Finally, tensor computations are performed on the graph features of two faces, and the aggregated features are extracted and discriminated by a fully connected layer to determine whether the individuals' identities are the same. Through various experimental tests, the network designed in this paper achieves an AUC index of 85.65% for facial keypoint localization on the 300W public dataset and 88.92% on a self-built dataset. In terms of face recognition accuracy, the proposed network achieves an accuracy of 83.41% on the IBUG public dataset and 96.74% on a self-built dataset. Experimental results demonstrate that the network designed in this paper exhibits high detection and recognition accuracy for faces in surveillance videos.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.10
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• pp.2632-2649
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• 2012

Most approaches to human action recognition is limited due to the use of simple action datasets under controlled environments or focus on excessively localized features without sufficiently exploring the spatio-temporal information. This paper proposed a framework for recognizing realistic human actions. Specifically, a new action representation is proposed based on computing a rich set of descriptors from keypoint trajectories. To obtain efficient and compact representations for actions, we develop a feature fusion method to combine spatial-temporal local motion descriptors by the movement of the camera which is detected by the distribution of spatio-temporal interest points in the clips. A new topic model called Markov Semantic Model is proposed for semantic feature selection which relies on the different kinds of dependencies between words produced by "syntactic " and "semantic" constraints. The informative features are selected collaboratively based on the different types of dependencies between words produced by short range and long range constraints. Building on the nonlinear SVMs, we validate this proposed hierarchical framework on several realistic action datasets.

• Journal of Korean Medical classics
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• v.19 no.3
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• pp.314-364
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• 2006

This thesis is a study on the Significance of Pulse in Internal Classic(內經脈義) in the Chapters on Vitality of Pulse(脈神章) in the Complete Works of Zhang Jingyue(景岳全書) Vol. IV. The Complete Works of Zhang Jingyue(景岳全書) is composed of 64 volumes. Maishenzhang, the Chapters on Vitality of Pulse(脈神章) is composed of 3 chapters. The first chapter is the Significance of Pulse in Internal Classic(內經服義). The terminology, Maishen(脈神) means the Vitality of Pulse, which was introduced by Zhang Jingyue to emphasize that the keypoint of sphygmological diagnosis is the vitality of pulse. The Significance of Pulse in Internal Classic(內經脈義) is composed of 20 parts including Buwei(部位), Maidu(脈度), Sanbujiuhou(三部九候), Qizhen(七診), Liujingmaoti(六經脈體), ect. in Miraculous Pivot(靈樞). There are no commentaries in most of them, which is because there are explanatory notes in Leijing(類經). Therefore, I referred to explanatory notes in Leijing(類經) to study the Significance of Pulse in Internal Classic(內經脈義), and make a study as followings.

• Ocean and Polar Research
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• v.37 no.1
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• pp.11-22
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• 2015

In-situ measurements are labor-intensive, time-consuming, and limited in their ability to observe currents with spatial variations in the surf zone. This paper proposes an optical image-based method of measurement of currents in the surf zone. This method measures nearshore currents by tracking in time wave breaking-induced foam patches from sequential images. Foam patches in images tend to be arrayed with irregular pixel intensity values, which are likely to remain consistent for a short period of time. This irregular intensity feature of a foam patch is characterized and represented as a keypoint using an image-based object recognition method, i.e., Scale Invariant Feature Transform (SIFT). The keypoints identified by the SIFT method are traced from time sequential images to produce instantaneous velocity fields. In order to remove erroneous velocities, the instantaneous velocity fields are filtered by binding them within upper and lower limits, and averaging the velocity data in time and space with a certain interval. The measurements that are obtained by this method are comparable to the results estimated by an existing image-based method of observing currents, named the Optical Current Meter (OCM).

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1993.04a
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• pp.93-100
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• 1993

With increasing technology, requirement to car noise and related dynamics are getting competitive keypoint. Unfortunately, vibro - acoustic behavior of a car is nowadays only possible after development of prototypes. But, obviously, in the Area of Research, many of Industrials, Universities and research centers try to codevelop the design tools to predict the vibro-acoustic behaviors. At this stage, it is more realistic to represent the existing technologies in order for the engineer to get their own know-how to design and to Integrate existing techniques, to setup their test facility, and to develope some tools with which they can successfully predict noise levels of car in the design phase. Moreover, most of the theories which will be represented in this paper can be used in the design phase. At any way, finding the cause of trouble shooting is more urgent than the design of a car to the test engineer. In this paper, transfer path analysis, noise source identification, and the key test method of modal analysis is introduced. Later, if I get the opportunity to present in KSNVE, the approach method of modal analysis is introduced. Later, if I get the opportunity to present in KSNVE, the approach method of finding characteristics of joint and welding part will be introduced. Most parts of this paper was quoted from the papers of LMS.

• Journal of Physiology & Pathology in Korean Medicine
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• v.31 no.4
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• pp.233-237
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• 2017

In this study, we report on the procedure of developing a guideline for clinical research protocol using moxibustion. Systematic review of the literature about moxibustion was conducted as a preliminary study to make basic content. Review and consulting by experts from each field was conducted to improve the quality. And we made checklist by arranging keypoint of this guideline. This guideline, Moxibustion Randomized Controlled Clinical Trial Guideline(MOXRATE), aims to be a guide for future researchers in planning clinical study using moxibustion as an intervention. MOXRATE also reports on an ethical issues.

• Journal of Information Processing Systems
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• v.14 no.1
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• pp.6-31
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• 2018

With the rapid development of the science and technology, it has been becoming more and more convenient to obtain abundant information via the diverse multimedia medium. However, the contents of the multimedia are easily altered with different editing software, and the authenticity and the integrity of multimedia content are under threat. Forensics technology is developed to solve this problem. We focus on reviewing the blind image forensics technologies for copy-move forgery in this survey. Copy-move forgery is one of the most common manners to manipulate images that usually obscure the objects by flat regions or append the objects within the same image. In this paper, two classical models of copy-move forgery are reviewed, and two frameworks of copy-move forgery detection (CMFD) methods are summarized. Then, massive CMFD methods are mainly divided into two types to retrospect the development process of CMFD technologies, including block-based and keypoint-based. Besides, the performance evaluation criterions and the datasets created for evaluating the performance of CMFD methods are also collected in this review. At last, future research directions and conclusions are given to provide beneficial advice for researchers in this field.