• Journal of Korea Multimedia Society
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• v.14 no.12
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• pp.1583-1590
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• 2011

A Certificate Revocation List(CRL) should be distributed quickly to all the vehicles for vehicular communications to protect them from malicious users and malfunctioning equipment as well as to increase the overall security and safety of vehicular networks. Thus, a major challenge in vehicular networks is how to efficiently distribute CRLs. This paper proposes a Multimedia Object Transfer(MOT) protocol based on CRL distribution scheme over T-DMB infrastructure. To complete the proposed scheme, a handoff method, CRL encoding rules based on the MOT protocol, and relative comparison are presented. The scheme can broaden breadth of network coverage and can get real-time delivery with enhanced transmission reliability. Even if road side units are sparsely deployed or, even not deployed, vehicles can obtain recent CRLs from T-DMB infrastructure effectively.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.1
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• pp.111-119
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• 2009

For daily life interaction with human, robots need the capability of encoding and storing cognitive information and retrieving it contextually. In this paper, spatiotemporal grounding of cognitive information for a language based cognitive system is presented. The cognitive information of the event occurred at a robot is described with a sentence, stored in a memory, and retrieved contextually. Each sentence is parsed, discriminated with the functional type of it, and analyzed with argument structure for connecting to cognitive information. With the proposed grounding, the cognitive information is encoded to sentence form and stored in sentence memory with object descriptor. Sentences are retrieved for answering questions of human by searching temporal information from the sentence memory and doing spatial reasoning in schematic imagery. An experiment shows the feasibility and efficiency of the spatiotemporal grounding for advanced service robot.

• ETRI Journal
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• v.44 no.1
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• pp.62-72
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• 2022

In this study, we propose a multi-GPU-based 8KVR stitching system that operates in real time on both local and cloud machine environments. The proposed system first obtains multiple 4 K video inputs, decodes them, and generates a stitched 8KVR video stream in real time. The generated 8KVR video stream can be downloaded and rendered omnidirectionally in player apps on smartphones, tablets, and head-mounted displays. To speed up processing, we adopt group-of-pictures-based distributed decoding/encoding and buffering with the NV12 format, along with multi-GPU-based parallel processing. Furthermore, we develop several algorithms such as equirectangular projection-based color correction, real-time CG overlay, and object motion-based seam estimation and correction, to improve the stitching quality. From experiments in both local and cloud machine environments, we confirm the feasibility of the proposed 8KVR stitching system with stitching speed of up to 83.7 fps for six-channel and 62.7 fps for eight-channel inputs. In addition, in an 8KVR live streaming test on the 5G MEC/cloud, the proposed system achieves stable performances with 8 K@30 fps in both indoor and outdoor environments, even during motion.

• Journal of Information Processing Systems
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• v.15 no.5
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• pp.1171-1178
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• 2019

This study proposes a deep neural network model based on an encoder-decoder structure for visual dialogs. Ongoing linguistic understanding of the dialog history and context is important to generate correct answers to questions in visual dialogs followed by questions and answers regarding images. Nevertheless, in many cases, a visual understanding that can identify scenes or object attributes contained in images is beneficial. Hence, in the proposed model, by employing a separate person detector and an attribute recognizer in addition to visual features extracted from the entire input image at the encoding stage using a convolutional neural network, we emphasize attributes, such as gender, age, and dress concept of the people in the corresponding image and use them to generate answers. The results of the experiments conducted using VisDial v0.9, a large benchmark dataset, confirmed that the proposed model performed well.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.37 no.4
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• pp.35-45
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• 2000

The vertex-based boundary encoding scheme is widely used in object-based video coding area and computer graphics due to its scalability with natural looking approximation. Existing single framebased vertex encoding algorithm is not efficient for temporally correlated video sequences because it does not remove temporal redundancy. In the proposed method, a vertex point is selected from not only the boundary points of the current frame but also the vertex points of the previous frame to remove temporal redundancy of shape information in video sequences. The problem of selecting optimal vertex points is modeled as finding shortest path in the directed acyclic graph with weight The boundary is approximated by a polygon which can be encoded with the smallest number of bits for maximum distortion. The temporal redundancy between two successive frames is efficiently removed with the proposed scheme, resulting in lower bit-rate than the conventional algorithms.

• Journal of KIISE:Information Networking
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• v.36 no.3
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• pp.198-203
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• 2009

With the growing demand for multimedia services and advances in display technology, new applications for 3$\sim$D scene communication have emerged. While multi-view video of these emerging applications may provide users with more realistic scene experience, drastic increase in the bandwidth is a major problem to solve. In this paper, we propose a fast prediction mode decision algorithm which can significantly reduce complexity and time consumption of the encoding process. This is based on the object segmentation, which can effectively identify the fast moving foreground object. As the foreground object with fast motion is more likely to be encoded in the view directional prediction mode, we can properly limit the motion compensated coding for a case in point. As a result, time savings of the proposed algorithm was up to average 45% without much loss in the quality of the image sequence.

• Journal of Broadcast Engineering
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• v.26 no.2
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• pp.175-183
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• 2021

The study of the fine grained classification of images continues to develop, but the study of object recognition for animals with polymorphic properties is proceeding slowly. Using only pet images corresponding to dogs and cats, this paper aims to compare methods using image processing and methods using deep learning among methods of classifying species of animals, which are fine grained classifications. In this paper, Grab-cut algorithm is used for object segmentation by method using image processing, and method using Fisher Vector for image encoding is proposed. Other methods used deep learning, which has achieved good results in various fields through machine learning, and among them, Convolutional Neural Network (CNN), which showed outstanding performance in image recognition, and Tensorflow, an open-source-based deep learning framework provided by Google. For each method proposed, 37 kinds of pet images, a total of 7,390 pages, were tested to verify and compare their effects.

• Journal of Microbiology and Biotechnology
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• v.17 no.10
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• pp.1727-1732
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• 2007

Phenylacetic acid (PAA) is produced by many bacteria as an antifungal agent and also appears to be an environmentally toxic chemical. The object of this study was to detect PAA using Pseudomonas putida harboring a reporter plasmid that has a PAA-inducible promoter fused to a green fluorescent protein (GFP) gene. Pseudomonas putida KT2440 was used to construct a green fluorescent protein-based reporter fusion using the paaA promoter region to detect the presence of PAA. The reporter strain exhibited a high level of gfp expression in minimal medium containing PAA; however, the level of GFP expression diminished when glucose was added to the medium, whereas other carbon sources, such as succinate and pyruvate, showed no catabolic repression. Interestingly, overexpression of a paaF gene encoding PAA-CoA ligase minimized catabolic repression. The reporter strain could also successfully detect PAA produced by other PAA-producing bacteria. This GFP-based bioreporter provides a useful tool for detecting bacteria producing PAA.

• Journal of KIISE:Databases
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• v.33 no.3
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• pp.299-309
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• 2006

Due to the rapid development in mobile communication technologies, the usage of mobile devices such as cell phone or PDA becomes increasingly popular. As different devices require different applications, various new services are being developed to satisfy the needs. One of the popular services under heavy demand is the Location-based Service (LBS) that exploits the spatial information of moving objects per temporal changes. In order to support LBS efficiently, it is necessary to be able to index and query well a large amount of spatio-temporal information of moving objects. Therefore, in this paper, we investigate how such location information of moving objects can be efficiently stored and indexed. In particular, we propose a novel location encoding method based on hierarchical administrative district information. Our proposal is different from conventional approaches where moving objects are often expressed as geometric points in two dimensional space, (x,y). Instead, in ours, moving objects are encoded as one dimensional points by both administrative district as well as road information. Our method is especially useful for monitoring traffic situation or tracing location of moving objects through approximate spatial queries.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.1
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• pp.13-20
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• 2004

In this paper, we have analyzed the current MPEG-4 video encoding tools and proposed efcient coding techniques that reduce the complexity of the encoder. Until recently, encoder optimization without shape coding has been a major concern in video for wire/wireless low bit rate coding services. Recently, we found out that the computational complexity of MPEG-4 shape coding plays a very important role in the object-based coding through experiments. We have made an experiment whether we could get optimized object-based coding method through successfully combining latest optimized texture coding techniques with our proposed optimized shape coding techniques. In texture coding, we applied the MVFAST method for motion estimation. We chose not to use IVOPF(Intelligent VOP Formation) but to use TRB(Tightest Rectangular Boundary) for positioning VOP and, finally, to eliminate the spiral search of shape motion estimation to reduce the complexity in shape coding. As a result of experiment, our proposed scheme achieved improved time complexity over the existing reference software by $57.3\%$ and over the optimized method on which only shape coding was applied by $48.7\%$, respectively.