• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.1
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• pp.111-120
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• 2015

HDR(High dynamic range) imaging is a technique to represent a dynamic range of real world. Exposure fusion is a method to obtain a pseudo-HDR image and it directly fuses multi-exposure images instead of generating the true-HDR image. However, it results ghost artifacts while fusing the multi-exposure images with moving objects. To solve this drawback, temporal consistency assessment is proposed to remove moving objects. Firstly, multi-level threshold bitmap and brightness bitmap are proposed. In addition, hue-angle constancy map between multi-exposure images is proposed for compensating a bitmap. Then, two bitmaps are combined as a temporal weight map. Spatial domain image quality assessment is used to generate a spatial weight map. Finally, two weight maps are applied at each multi-exposure image and combined to get the pseudo-HDR image. In experiments, the proposed method reduces ghost artifacts more than previous methods. The quantitative ghost-free evaluation of the proposed method is also less than others.

• Journal of Broadcast Engineering
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• v.13 no.5
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• pp.732-743
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• 2008

In H.264/AVC, 4$\times$4 block transform is used for intra and inter prediction instead of 8$\times$8 block transform. Using small block size coding, H.264/AVC obtains high temporal prediction efficiency, however, it has limitation in utilizing spatial redundancy. Motivated on these points, we propose a multi-dimensional transform which achieves both the accuracy of temporal prediction as well as effective use of spatial redundancy. From preliminary experiments, the proposed multi-dimensional transform achieves higher energy compaction than 2-D DCT used in H.264. We designed an integer-based transform and quantization coder for multi-dimensional coder. Moreover, several additional methods for multi-dimensional coder are proposed, which are cube forming, scan order, mode decision and updating parameters. The Context-based Adaptive Variable-Length Coding (CAVLC) used in H.264 was employed for the entropy coder. Simulation results show that the performance of the multi-dimensional codec appears similar to that of H.264 in lower bit rates although the rate-distortion curves of the multi-dimensional DCT measured by entropy and the number of non-zero coefficients show remarkably higher performance than those of H.264/AVC. This implies that more efficient entropy coder optimized to the statistics of multi-dimensional DCT coefficients and rate-distortion operation are needed to take full advantage of the multi-dimensional DCT. There remains many issues and future works about multi-dimensional coder to improve coding efficiency over H.264/AVC.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.04a
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• pp.739-742
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• 1997

A remote drum grappling device coupled to the anti-swing crane has been developed by KAERI to cope with problems involved in manually treating low level waste drums. In order for this grappling device to be operated effectively, multi-sensors including CCD camera were employed. As an activity representation scheme of the device, Extended State Machine (ESM) was used to descibe its operation sequences. The performance testing of the device was conducted successfully, and consequently its application could be extendable to industrial operation environment.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.3
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• pp.1434-1449
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• 2019

Video object segmentation is a significant task in computer vision, but its performance is not very satisfactory. A method of video object segmentation using weakly temporal information is presented in this paper. Motivated by the phenomenon in reality that the motion of the object is a continuous and smooth process and the appearance of the object does not change much between adjacent frames in the video sequences, we use a feed-forward architecture with motion estimation to predict the mask of the current frame. We extend an additional mask channel for the previous frame segmentation result. The mask of the previous frame is treated as the input of the expanded channel after processing, and then we extract the temporal feature of the object and fuse it with other feature maps to generate the final mask. In addition, we introduce multi-mask guidance to improve the stability of the model. Moreover, we enhance segmentation performance by further training with the masks already obtained. Experiments show that our method achieves competitive results on DAVIS-2016 on single object segmentation compared to some state-of-the-art algorithms.

• The Journal of the Acoustical Society of Korea
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• v.29 no.2
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• pp.133-140
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• 2010

We improve the performance of cardiac disorder classification by adding new temporal features extracted from continuous heart sound signals. We add three kinds of novel temporal features to a conventional feature based on mel-frequency cepstral coefficients (MFCC): Heart sound envelope, murmur probabilities, and murmur amplitude variation. In cardiac disorder classification and detection experiments, we evaluate the contribution of the proposed features to classification accuracy and select proper temporal features using the sequential feature selection method. The selected features are shown to improve classification accuracy significantly and consistently for neural network-based pattern classifiers such as multi-layer perceptron (MLP), support vector machine (SVM), and extreme learning machine (ELM).

• Cartoon and Animation Studies
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• s.48
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• pp.69-84
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• 2017

In order to display various art works such as media art in a multi-display environment, it is necessary to consider contents arrangement. The advantage of having a 1: N or N: N layout instead of a 1: 1 or N: 1 layout between display and content, but a more complex scheme of how to do spatial and temporal layout in multi-display Is required. In order to distribute contents, existing media server solution or programming-based multimedia production software is used. However, it takes much time to rearrange or modify the contents, and it is not easy to modify the contents. Therefore, It is difficult to place content in the environment. In order to solve this problem, various approaches are needed from research on content placement method to development of content placement software that improves the existing method. However, analysis on systematic content placement type supporting it, or interface There is also no access to. In this study, we have summarized the requirements for designing the interface for each type with the aim of making it possible to utilize previously analyzed content layout types in various display activities such as media art in multi - display environment. The requirements of each type of interface were derived based on spatial arrangement and temporal layout type which are most distinguished when content is placed. The contents of the interface requirements are summarized as follows: We expect to be a cornerstone for system development.

• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.4
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• pp.52-67
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• 2020

Recently, the Arctic has been exposed to snow-covered land due to melting permafrost every year, and the Korea Geographic Information Institute(NGII) provides polar spatial information service by establishing spatial information of the polar region. However, there is a lack of spatial information on vegetation sensitive to climate change. This research used a multi-temporal Sentinel-2 image to perform land cover classification of the Ny-Ålesund in Arctic Svalbard. In the pre-processing step, 10 bands and 6 vegetation spectral index were generated from multi-temporal Sentinel-2 images. In image-classification step is consisted of extracting the vegetation area through 8-class land cover classification and performing the vegetation species classification. The image classification algorithm used Random Forest to evaluate the accuracy and calculate feature importance through Out-Of-Bag(OOB). To identify the advantages of multi- temporary Sentinel-2 for vegetation classification, the overall accuracy was compared according to the number of images stacked and vegetation spectral index. Overall accuracy was 77% when using single-time Sentinel-2 images, but improved to 81% when using multi-time Sentinel-2 images. In addition, the overall accuracy improved to about 83% in learning when the vegetation index was used additionally. The most important spectral variables to distinguish between vegetation classes are located in the Red, Green, and short wave infrared-1(SWIR1). This research can be used as a basic study that optimizes input characteristics in performing the classification of vegetation in the polar regions.

• Journal of KIISE
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• v.43 no.12
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• pp.1365-1375
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• 2016

One of the most important capabilities for autonomous service robots working in living environments is to recognize and understand the correct context in dynamically changing environment. To generate high-level context knowledge for decision-making from multiple sensory data streams, many technical problems such as multi-modal sensory data fusion, uncertainty handling, symbolic knowledge grounding, time dependency, dynamics, and time-constrained spatio-temporal reasoning should be solved. Considering these problems, this paper proposes an effective dynamic context management and spatio-temporal reasoning method for intelligent service robots. In order to guarantee efficient context management and reasoning, our algorithm was designed to generate low-level context knowledge reactively for every input sensory or perception data, while postponing high-level context knowledge generation until it was demanded by the decision-making module. When high-level context knowledge is demanded, it is derived through backward spatio-temporal reasoning. In experiments with Turtlebot using Kinect visual sensor, the dynamic context management and spatio-temporal reasoning system based on the proposed method showed high performance.

• Journal of Internet Computing and Services
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• v.7 no.1
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• pp.17-30
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• 2006

With the wide acceptance of the Internet and the Web, volumes of information and related users have increased and companies have become to need security mechanisms to effectively protect important information for business activities and security problems have become increasingly difficult. This paper proposes a improved access control model for access control enforcement in enterprise environments through the integration of the temporal constraint character of the GT-RBAC model. sub-role hierarchies concept and PBDM(Permission Based Delegation Model). The proposed model. called Extended GT-RBAC(Extended Generalized Temporal Role Based Access Control) delegation Model. supports characteristics of GTRBAC model such as of temporal constraint, various time-constrained cardinality, control flow dependency and separation of duty constraints (SoDs). Also it supports conditional inheritance based on the degree of inheritance and business characteristics by using sub-roles hierarchies and supports permission based delegation, user to user delegation, role to role delegation, multi-step delegation and temporal delegation by using PBDM.

• Journal of Digital Contents Society
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• v.8 no.4
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• pp.441-449
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• 2007

In video coding, motion estimation is a process to estimate the pixel of the current frame from the reference frame, which affects directly the predictive quality and the encoding time. This paper is related to AHHS(Adaptive Hierarchical Hexagon Search) using spatio-temporal motion activity for fast motion estimation. The proposed method defines the spatio-temporal motion activity of the current macroblock using the motion vectors of its spatio-temporally adjacent macroblocks, and then conventional AHS(Adaptive Hexagon Search) is performed if the spatio-temporal motion activity is lower, otherwise, hierarchical hexagon search is performed on a multi-layered hierarchical space constructed by multiple sub-images with low frequency in wavelet transform. In the paper, based on computer simulation results for multiple video sequences with different motion characteristics, the performance of the proposed method was analysed and assessed in terms of the predictive quality and the computational time. Experimental results indicate that the proposed method is both suitable for (quasi-) stationary and large motion searches. The proposed method could keep the merit of the adaptive hexagon search capable of fast estimating motion vectors and also adaptively reduce the local minima occurred in the video sequences with higher spatio-temporal motion activity.