• Journal of Internet Computing and Services
• /
• v.20 no.1
• /
• pp.47-55
• /
• 2019

Free-viewpoint video (FVV) service provides multi viewpoints of contents and synthesizes intermediate video files which are not captured on some view angles so that enables users to watch as they choose wherever they want. Synthesizing video is necessary technique to provide FVV video service, because every video of the FVV contents for different view angles cannot be stored to the content server physically. For the reason, fast view synthesis can improve the quality of video service and increase user's satisfaction. One of the studies for FVV service, a method was proposed to transmit FVV service based on DASH (Dynamic Adaptive Streaming over HTTP). There is big advantage on using DASH that it is commonly used to transport video service. However, the method was only a conceptual proposal, so it is difficult to implement the system using the proposal. In this paper, we propose an implementation method to provide real-time FVV service smoothly. We suggest a system structure and operation method on the server and client side in detail, which is to be applicable to synthesize video quickly. Also, we suggest generating FVV service map additionally which controls a FVV service overall. We manage real-time information of the whole service through the service map. The service can be controlled by reducing the possible delay from network situation.

• Journal of Korea Multimedia Society
• /
• v.8 no.6
• /
• pp.744-752
• /
• 2005

When the multiple video sources are transmitted together through the channel of fixed bandwidth, an efficient picture quality control is necessary. This paper presents a joint picture quality control method to satisfy the user requirement by priority among the video sources. The better picture quality is assigned to the source of higher priority compared to lower priority. We obtain the bitrate for each source to have a required distortion level among the sources by using an approximate distortion-bitrate model for simple implementation. It is shown by simulation that the proposed bandwidth allocation method can keep almost the user-required picture quality among the sources in comparison to an independent bandwidth allocation method.

• Journal of Korea Multimedia Society
• /
• v.21 no.7
• /
• pp.755-763
• /
• 2018

In this paper, for recognize a night pedestrian from an infrared video, a new method differentiated from the existing feature vector is proposed and experimented. The new approach focuses on the shape feature vector of the structure and shape of the pedestrian image divided by the human body seven split ratio. The pedestrian images are divided into 7 square blocks from the still image of the preprocessing process. And to reduce the dimension, the square block is converted into a mosaic block. The scalar and direction of the shape feature vector is calculated by the brightness and position of the element in the mosaic. For practicality of infrared video system, the proposed method simplifies the data to be processed by reducing the amount of data in the preprocessing in order to continuously batch process the entire system in real time. Through the experiments, we verified the validity of the proposed shape feature vector. In comparison to the existing method, we propose a new shape feature vector generation method as the feature vector for night pedestrian recognition.

• ETRI Journal
• /
• v.43 no.3
• /
• pp.538-548
• /
• 2021

This paper proposes an approach to improve the performance of no-reference video quality assessment for sports videos with dynamic motion scenes using an efficient spatiotemporal model. In the proposed method, we divide the video sequences into video blocks and apply a 3D shearlet transform that can efficiently extract primary spatiotemporal features to capture dynamic natural motion scene statistics from the incoming video blocks. The concatenation of a deep residual bidirectional gated recurrent neural network and logistic regression is used to learn the spatiotemporal correlation more robustly and predict the perceptual quality score. In addition, conditional video block-wise constraints are incorporated into the objective function to improve quality estimation performance for the entire video. The experimental results show that the proposed method extracts spatiotemporal motion information more effectively and predicts the video quality with higher accuracy than the conventional no-reference video quality assessment methods.

• Proceedings of the IEEK Conference
• /
• 2000.07b
• /
• pp.835-838
• /
• 2000

Popular methods for extracting a text region in video images are in general based on analysis of a whole image such as merge and split method, and comparison of two frames. Thus, they take long computing time due to the use of a whole image. Therefore, this paper suggests the faster method of extracting a text region without processing a whole image. The proposed method uses line sampling methods, FFT and neural networks in order to extract texts in real time. In general, text areas are found in the higher frequency domain, thus, can be characterized using FFT The candidate text areas can be thus found by applying the higher frequency characteristics to neural network. Therefore, the final text area is extracted by verifying the candidate areas. Experimental results show a perfect candidate extraction rate and about 92% text extraction rate. The strength of the proposed algorithm is its simplicity, real-time processing by not processing the entire image, and fast skipping of the images that do not contain a text.

• Journal of Yeungnam Medical Science
• /
• v.35 no.1
• /
• pp.63-69
• /
• 2018

Background: Kinovea software that tracking semi-automatically the motion in video screen has been used to study motion-related tasks in several studies. However, the validation of this software in open field test to assess locomotor activity have not been studied yet. Therefore, this study aimed to examine the reliability and validity of this software in analyzing locomotor activities. Methods: Thirty male Institute Cancer Research mice were subjected in this study. The results examined by this software and the classical method were compared. Test-retest reliability and inter-rater reliability were analyzed with Pearson's correlation coefficient and intraclass correlation coefficient (ICC). The validity of this software was analyzed with Pearson's correlation coefficient. Results: This software showed good test-retest reliability (ICC=0.997, 95% confidence interval [CI]=0.975-0.994, p<0.001). This software also showed good inter-rater reliability (ICC=0.987, 95% CI=0.973-0.994, p<0.001). Furthermore, in three analyses for the validity of this software, there were significant correlations between two methods (Pearson's correlation coefficient=0.928-0.972, p<0.001). In addition, this software showed good reliability and validity in the analysis locomotor activity according to time interval. Conclusion: This study showed that this software in analyzing drug-induced locomotor activity has good reliability and validity. This software can be effectively used in animal study using the analysis of locomotor activity.

• Journal of KIISE:Software and Applications
• /
• v.35 no.12
• /
• pp.753-763
• /
• 2008

The amount of UCCs (User Created Contents) has been increasing rapidly and is associated with a serious copyright problem. Automatic logo detection in videos is an efficient means of overcoming the copyright problem. However, logos have varying characteristics, which make logo detection and recognition very difficult. Especially, there are frequent logo transitions in a video, comprising several video contents. This disrupts accurate video segmentation based on logos. Therefore, this paper proposes an accurate logo transition detection method for recognizing logos in digital video contents. The proposed method accurately segments a video according to logo and efficiently recognizes various types of logos. The experimental results demonstrate the effectiveness of the proposed method for logo detection and video segmentation according to logo.

• Journal of The Korean Association of Information Education
• /
• v.19 no.4
• /
• pp.441-448
• /
• 2015

This paper describes about a software implementation for class analysis and quantization based on our video synchronization method. We proposed a new indexing method, synchronization strategies, and data structure for our analyzer implementation. We implemented a class video analyzer using intelligent multimedia technologies which can play class video selectively. Our proposed method analyzes class videos depending on the time schedule composed of introduction, development and summary stages. We apply our analysis filters to the class videos in the predefined regular intervals. We experimented on the synchronization performance of our proposed method and software. In the experimental, we could demonstrate the effectiveness and practicality of our class analyzing method within the margin of error.

• Journal of Broadcast Engineering
• /
• v.7 no.2
• /
• pp.107-113
• /
• 2002

In this paper, we propose a method and a software system for automatic summarization of baseball game videos. The proposed system pursues fast execution and high accuracy of summarization. To satisfy the requirement, the detection of important events in baseball video is performed through DC-based shot boundary detection algorithm and simple caption recognition method. Furthermore, the proposed system supports a hierarchical description so that users can browse and navigate videos in several levels of summarization. In this paper, we propose a method and a software system for automatic summarization of baseball game videos. The proposed system pursues fast execution and high accuracy of summarization. To satisfy the requirement, the detection of important events in baseball video is performed through DC-based shot boundary detection algorithm and simple caption recognition method. Furthermore, the proposed system supports a hierarchical description so that users can browse and navigate videos in several levels of summarization.

• International journal of advanced smart convergence
• /
• v.9 no.4
• /
• pp.124-131
• /
• 2020

As users of internet-based software applications increase, functional and non-functional problems for software applications are quickly exposed to user reviews. These user reviews are an important source of information for software improvement. User review mining has become an important topic of intelligent software engineering. This study proposes a user review mining method for software improvement. User review data collected by crawling on the app review page is analyzed to check user satisfaction. It analyzes the sentiment of positive and negative that users feel with a machine learning method. And it analyzes user requirement issues through topic analysis based on structural topic modeling. The user review mining process proposed in this study conducted a case study with the a non-face-to-face video conferencing app. Software improvement through user review mining contributes to the user lock-in effect and extending the life cycle of the software. The results of this study will contribute to providing insight on improvement not only for developers, but also for service operators and marketing.