• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.7
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• pp.3018-3038
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• 2020

In the stereoscopic or multiview display, the depth video illustrates visual distances between objects and camera. To promote the computational efficiency of depth video encoder, we exploit the intra prediction of depth videos under Versatile Video Coding (VVC) and observe a diverse distribution of intra prediction modes with different coding unit sizes. We propose a hybrid scheme to further boost fast depth video coding. In the first stage, we adaptively predict the HADamard (HAD) costs of intra prediction modes and initialize a candidate list according to the HAD costs. Then, the candidate list is further improved by considering the probability distribution of candidate modes with different CU sizes. Finally, early termination of CU splitting is performed at each CU depth level based on the Bayesian theorem. Our proposed method is incorporated into VVC intra prediction for fast coding of depth videos. Experiments with 7 standard sequences and 4 Quantization parameters (Qps) validate the efficiency of our method.

• Journal of Korea Spatial Information System Society
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• v.11 no.2
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• pp.111-118
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• 2009

Recently many global enterprises build RTLS system for their environments. RTLS is used to detect object at real tim e. Unlike RFID, RTLS tags are read automatically and continuously, independent of the process that moves the tags. The proposed functionality of standard API has two problems. When middleware provides data to application, it sends a huge amount of data that may be useless. When only an application requests for data, the middleware replies result data in synchronous mode. This paper proposes a method to reduce an amount of data transferring from middleware to application and an addition communication mode to support real-time event processing in the middleware. Also, we designed and implemented an RTLS middleware applying the proposed methods.

• Journal of Information Processing Systems
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• v.11 no.1
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• pp.39-56
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• 2015

Continuous multi-interval prediction (CMIP) is used to continuously predict the trend of a data stream based on various intervals simultaneously. The continuous integrated hierarchical temporal memory (CIHTM) network performs well in CMIP. However, it is not suitable for CMIP in real-time mode, especially when the number of prediction intervals is increased. In this paper, we propose a real-time integrated hierarchical temporal memory (RIHTM) network by introducing a new type of node, which is called a Zeta1FirstSpecializedQueueNode (ZFSQNode), for the real-time continuous multi-interval prediction (RCMIP) of data streams. The ZFSQNode is constructed by using a specialized circular queue (sQUEUE) together with the modules of original hierarchical temporal memory (HTM) nodes. By using a simple structure and the easy operation characteristics of the sQUEUE, entire prediction operations are integrated in the ZFSQNode. In particular, we employed only one ZFSQNode in each level of the RIHTM network during the prediction stage to generate different intervals of prediction results. The RIHTM network efficiently reduces the response time. Our performance evaluation showed that the RIHTM was satisfied to continuously predict the trend of data streams with multi-intervals in the real-time mode.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.5
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• pp.796-804
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• 1994

This paper presents Inverse SAR imaging algorithm for a unknown velocity target and a real ISAR data is processed and applied to the algorithm. The real ISAR data is obtained by transmitting a number of pulse modulated by a stepped-frequency method and the received data are undersampled. We present a method applicable for the case of a undersampled data base. In this method, the original echoed signal is mixed with a reference signal to make it unaliased, followed by being interpolated. Target`s velocity required for the algorithm is estimated via subaperture processing and after the coordinate transformation into squint-mode SAR with the estimated velocity, a recently proposed SAR/ISAR imaging algorithm derived without any approximation is utilized to produce the output image. We also propose an ISAR image scheme that is usable when a target changes its velocity during ISAR data acquisition time.

• Journal of Information Processing Systems
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• v.10 no.2
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• pp.176-192
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• 2014

The realization of Wireless Multimedia Sensor Networks (WMSNs) has been fostered by the availability of low cost and low power CMOS devices. However, the transmission of bulk video data requires adequate bandwidth, which cannot be promised by single path communication on an intrinsically low resourced sensor network. Moreover, the distortion or artifacts in the video data and the adherence to delay threshold adds to the challenge. In this paper, we propose a two stage Quality of Service (QoS) guaranteeing scheme called Prioritized Multipath WMSN (PMW) for transmitting H.264 encoded video. Multipath selection based on QoS metrics is done in the first stage, while the second stage further prioritizes the paths for sending H.264 encoded video frames on the best available path. PMW uses two composite metrics that are comprised of hop-count, path energy, BER, and end-to-end delay. A color-coded assisted network maintenance and failure recovery scheme has also been proposed using (a) smart greedy mode, (b) walking back mode, and (c) path switchover. Moreover, feedback controlled adaptive video encoding can smartly tune the encoding parameters based on the perceived video quality. Computer simulation using OPNET validates that the proposed scheme significantly outperforms the conventional approaches on human eye perception and delay.

• Journal of Information Processing Systems
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• v.17 no.4
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• pp.754-771
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• 2021

In the task of continuous dimension emotion recognition, the parts that highlight the emotional expression are not the same in each mode, and the influences of different modes on the emotional state is also different. Therefore, this paper studies the fusion of the two most important modes in emotional recognition (voice and visual expression), and proposes a two-mode dual-modal emotion recognition method combined with the attention mechanism of the improved AlexNet network. After a simple preprocessing of the audio signal and the video signal, respectively, the first step is to use the prior knowledge to realize the extraction of audio characteristics. Then, facial expression features are extracted by the improved AlexNet network. Finally, the multimodal attention mechanism is used to fuse facial expression features and audio features, and the improved loss function is used to optimize the modal missing problem, so as to improve the robustness of the model and the performance of emotion recognition. The experimental results show that the concordance coefficient of the proposed model in the two dimensions of arousal and valence (concordance correlation coefficient) were 0.729 and 0.718, respectively, which are superior to several comparative algorithms.

• Journal of Information Processing Systems
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• v.11 no.1
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• pp.22-38
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• 2015

While Modern Standard Arabic is the formal spoken and written language of the Arab world; dialects are the major communication mode for everyday life. Therefore, identifying a speaker's dialect is critical in the Arabic-speaking world for speech processing tasks, such as automatic speech recognition or identification. In this paper, we examine two approaches that reduce the Universal Background Model (UBM) in the automatic dialect identification system across the five following Arabic Maghreb dialects: Moroccan, Tunisian, and 3 dialects of the western (Oranian), central (Algiersian), and eastern (Constantinian) regions of Algeria. We applied our approaches to the Maghreb dialect detection domain that contains a collection of 10-second utterances and we compared the performance precision gained against the dialect samples from a baseline GMM-UBM system and the ones from our own improved GMM-UBM system that uses a Reduced UBM algorithm. Our experiments show that our approaches significantly improve identification performance over purely acoustic features with an identification rate of 80.49%.

• The Transactions of the Korea Information Processing Society
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• v.3 no.7
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• pp.1858-1867
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• 1996

This paper describes a platform for video conferencing on Information Super Highway. In this paper we de-sign a Multi-Multicast Server(MCS) and the platform. The platform uses Multi-MultiCast Server for multitasking IP Multicast data on IP over ATM. Based on Multicast Address Resolution Server (AMRS) which was proposed in this paper the platform maps from D class IP addresses to ATM addresses. MARS handles a recovery in case of MCS down. This paper also presents a solving mechanism for handling botteneck by using the MCS.

• Proceedings of the Korea Information Processing Society Conference
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• 2017.11a
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• pp.134-137
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• 2017

Follow-me function of drones is new and attractive for selfie drone users, where the drone autonomously follows and capture the user. Currently the products use the difference between GPS's in the drone and user side mobile GCS, but the targeting accuracy is not satisfactory owing to the low accuracy of GPS data, often the order of ten meters. We designed a new follow-me mode algorithm that utilizes the accuracy of visual tracking algorithm and the reliability of GPS-based. The experiment shows that proposed follow-me can capture much accurately the target user in the center of video content than GPS-only methods, and recover the vision algorithm failure quickly in 5-10 seconds.

• Proceedings of the Korea Information Processing Society Conference
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• 2017.11a
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• pp.1254-1257
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• 2017

LoRa는 저전력 및 장거리 작동을 위해 설계된 새로운 ISM 대역 무선 기술이며, LoRaWAN은 LoRa에서 정의된 광역 네트워크 프로토콜이다. 본 논문에서는 실제 환경에서 LoRaWAN 기술의 통신 성능을 검증하는 것을 목표로 한다. 이를 위해, 캠퍼스 내에 LoRaWAN 실험을 위한 실제 테스트 베드를 구축했다. 사용자들이 사용하는 실제 환경을 만들기 위해 통신 게이트웨이를 실내에 설치하였고, 캠퍼스의 실내외 다수 위치에서 데이터를 P2P 방식으로 게이트웨이에게 전송한다. 실험에서는 대역폭, 코딩 속도, 확산 계수 및 전송 전력을 변화시켰으며, 성능 검증을 위해 신호대잡음비와 패킷 전송률을 측정하여 결과를 분석한다.