• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.29 no.10C
• /
• pp.1469-1483
• /
• 2004

We propose a packet scheduling algorithms for streaming media. We assume that the receiver periodically reports back the channel throughput. From the original video data, the importance level of a video packet is determined by its relative position within its group of pictures, taking into account the motion-texture discrimination and temporal scalability. Thus, we generate a number of nested substreams. Using feedback information from the receiver and statistical characteristics of the video, we model the streaming system as a queueing system, compute the run-time decoding failure probability of a Same in each substream based on effective bandwidth approach, and determine the optimum substream to be sent at that moment in time. Since the optimum substream is updated periodically, the resulting sending order is different from the original playback order. From experiments with real video data, we show that our proposed scheduling scheme outperforms the conventional sequential sending scheme.

• Journal of Intelligence and Information Systems
• /
• v.16 no.2
• /
• pp.95-108
• /
• 2010

In this paper, we present a hybrid neural network model for dynamic hand gesture recognition. The model consists of two modules, feature extraction module and pattern classification module. We first propose a modified CNN(convolutional Neural Network) a pattern recognition model for the feature extraction module. Then we introduce a weighted fuzzy min-max(WFMM) neural network for the pattern classification module. The data representation proposed in this research is a spatiotemporal template which is based on the motion information of the target object. To minimize the influence caused by the spatial and temporal variation of the feature points, we extend the receptive field of the CNN model to a three-dimensional structure. We discuss the learning capability of the WFMM neural networks in which the weight concept is added to represent the frequency factor in training pattern set. The model can overcome the performance degradation which may be caused by the hyperbox contraction process of conventional FMM neural networks. From the experimental results of human action recognition and dynamic hand gesture recognition for remote-control electric home appliances, the validity of the proposed models is discussed.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.22 no.4
• /
• pp.617-623
• /
• 2018

In this paper, we propose a novel seamless video composition method based on shape matching and Poisson equation. Video composition method consists of video segmentation process and video blending process. In the video segmentation process, the user first sets a trimap for the first frame, and then performs a grab-cut algorithm. Next, considering that the performance of video segmentation may be reduced if the color, brightness and texture of the object and the background are similar, the object region segmented in the current frame is corrected through shape matching between the objects of the current frame and the previous frame. In the video blending process, the object of source video and the background of target video are blended seamlessly using Poisson equation, and the object is located according to the movement path set by the user. Simulation results show that the proposed method has better performance not only in the naturalness of the composite video but also in computational time.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.21 no.2
• /
• pp.429-434
• /
• 2017

In a graph G=(V, E) with n vertices, there is an unique box which is finally laid on each vertex. Thus each vertex and box is both numbered from 1 to n and the box i should be laid on the vertex i. But, the box ${\pi}$(i) is initially located on the vertex i according to a permutation ${\pi}$. In each step, the robot can walk along an edge of G and can carry at most one box at a time. Also when arriving at a vertex, the robot can swap the box placed there with the box it is carrying. The problem is to minimize the total step so that every vertex has its own box, that is, the shuffled boxes are sorted. In this paper, we shall find an upper bound of the minimum number of steps and show that the movement of the robot is found in $O(n^2)$ time when G is a cycle.

• The KIPS Transactions:PartB
• /
• v.18B no.1
• /
• pp.39-44
• /
• 2011

In this paper, we propose a method to improve the Firefly Algorithm(FA) introduced by Xin-She Yang, recently. We design and analyze the improved firefly algorithm based on the heuristic. We compare the FA with the Particle Swarm Optimization (PSO) which the problem domain is similar with the FA in terms of accuracy, algorithm convergence time, the motion of each particle. The compare experiments show that the accuracy of FA is not worse than PSO's, but the convergence time of FA is slower than PSO's. In this paper, we consider intuitive reasons of slow convergence time problem of FA, and propose the improved version of FA using a partial mutation heuristic based on the consideration. The experiments using benchmark functions show the accuracy and convergence time of the improved FA are better than them of PSO and original FA.

• Journal of Broadcast Engineering
• /
• v.13 no.1
• /
• pp.137-151
• /
• 2008

H.264/AVC is showed high coding efficiency more than previous video coding standard by using new coding tools. Specially, Variable block-based motion estimation and Rate-Distortion Optimization are very important coding tools in H.264/AVC. These coding tools have high coding efficiency, however the encoder complexity greatly increase due to these coding tools. In this paper, we propose early SKIP mode decision and selective inter/intra mode decision to reduce the computational complexity. Simulation results show that the proposed method could reduce encoding time of the overall sequences by 30% on average than JM 10.2 without noticeable degradation of coding efficiency. Besides, the proposed method runs over twice as fast as the previous proposed Fast Coding Mode Selection method (FCMS)[5].

• Journal of KIISE:Information Networking
• /
• v.36 no.3
• /
• pp.198-203
• /
• 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 Korea Multimedia Society
• /
• v.3 no.2
• /
• pp.121-132
• /
• 2000

Most of video indexing applications depend on fast and efficient archiving, browsing, retrieval techniques. A number of techniques have been approached about only pixel domain analysis until now. Those approaches brought about the costly overhead of decompressing because the most of multimedia data is typically stored in compressed format. But with a compressed video data, if we can analyze the compressed data directly. then we avoid the costly overhead such as in pixel domain. In this paper, we analyze the information of compressed video stream directly, and then extract the available features for video indexing. We have derived the technique for cut detection using these features, and the stream is divided into shots. Also we propose a new brief key frame selection technique and an efficient video indexing method using the spatial informations(DT coefficients) and also the temporal informations(motion vectors).

• Journal of Game and Entertainment
• /
• v.2 no.2
• /
• pp.61-69
• /
• 2006

Along with advance in visual culture, the importance of motion graphic has been increasingly emphasized day by day, which can maximize information delivery using image illustration and typography, graphic factors of images. In addition, we can easily see increasing cases where what a designer intends is visualized using creative typography in diverse mass media such as TV commercials, movies or web. Thanks to the effects of this trend, various ways of manufacturing works have been proposed in the field of motion typography by applying diverse factors including verbal ones, time, form, motion, colors, and sound for the purpose of expressing formless semantic notions through visual form of typography. However, physiological features such as sex, age, health status, pathological conditions, and body size can have a bigger effect on the process of real communication. Therefore, if property of quasi-verbal sound can be reflected appropriately in motion typography where communication is expressed only by visual form, it can enable people to understand what a designer intends faster and more exactly.

• KIPS Transactions on Software and Data Engineering
• /
• v.2 no.1
• /
• pp.27-34
• /
• 2013

Background subtraction is one of the key techniques for automatic video content analysis, especially in the tasks of visual detection and tracking of moving object. In this paper, we present a new sample-based technique for background extraction that provides background image as well as background model. To handle both high-frequency and low-frequency events at the same time, multiple interval background models are adopted. The main innovation concerns the use of a confidence factor to select the best model from the multiple interval background models. To our knowledge, it is the first time that a confidence factor is used for merging several background models in the field of background extraction. Experimental results revealed that our approach based on multiple interval sampling works well in complicated situations containing various speed moving objects with environmental changes.