• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.9
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• pp.3196-3210
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• 2014

This paper presents a novel video metrology approach based on robust tracking. From videos acquired by an uncalibrated stationary camera, the foreground likelihood map is obtained by using the Codebook background modeling algorithm, and the multiple moving objects are tracked by a combined tracking algorithm. Then, we compute vanishing line of the ground plane and the vertical vanishing point of the scene, and extract the head feature points and the feet feature points in each frame of video sequences. Finally, we apply a single view mensuration algorithm to each of the frames to obtain height measurements and fuse the multi-frame measurements using RANSAC algorithm. Compared with other popular methods, our proposed algorithm does not require calibrating the camera, and can track the multiple moving objects when occlusion occurs. Therefore, it reduces the complexity of calculation and improves the accuracy of measurement simultaneously. The experimental results demonstrate that our method is effective and robust to occlusion.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1998.06b
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• pp.122-127
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• 1998

In this paper, we focus on the information retrieval of human individuals who are recorded on the video database. Our purpose is to index persons by their faces or voice and to retrieve their existing time sections on the video data. The database system can track as well as extract a face or voice of a certain person and construct a model of the individual person in self-organization mode. If he appears again at different time, the system can put the mark of the same person to the associated frames. In this way, the same person can be retrieved even if the system does not know his exact name. As the face and speaker modeling, a subspace method is employed to improve the indexing accuracy.

• Journal of Information Processing Systems
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• v.18 no.1
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• pp.130-145
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• 2022

Games are widely used in many fields, but not all games are successful. Then what makes games successful? The question gave us the motivation of this paper, which is to identify critical factors for successful games with topic modeling technique. It is supposed that game reviews written by experts sit on abundant insights and topics of how games succeed. To excavate these insights and topics, latent Dirichlet allocation, a topic modeling analysis technique, was used. This statistical approach provided words that implicate topics behind them. Fifty topics were inferred based on these words, and these topics were categorized by stimulation-response-desiregoal (SRDG) model, which makes a streamlined flow of how players engage in video games. This approach can provide game designers with critical factors for successful games. Furthermore, from this research result, we are going to develop a model for immersive game experiences to explain why some games are more addictive than others and how successful gamification works.

• Smart Media Journal
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• v.1 no.2
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• pp.12-22
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• 2012

Today we are witnessing an increasingly widespread use of cameras in our lives for video surveillance, robot vision, and mobile phones. This has led to a renewed interest in computer vision in general and an on-going boom in human activity recognition in particular. Although not particularly fancy per se, human gait is inarguably the most common and frequent action. Early on this decade there has been a passing interest in human gait recognition, but it soon declined before we came up with a systematic analysis and understanding of walking motion. This paper presents a set of DBN-based models for the analysis of human gait in sequence of increasing complexity and modeling power. The discussion centers around HMM-based statistical methods capable of modeling the variability and incompleteness of input video signals. Finally a novel idea of extending the discrete state Markov chain with a continuous density function is proposed in order to better characterize the gait direction. The proposed modeling framework allows us to recognize pedestrian up to 91.67% and to elegantly decode out two independent gait components of direction and posture through a sequence of experiments.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.10B
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• pp.1971-1978
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• 1999

In this paper, we study the effects of long-range dependence (LRD) in VBR video traffic on queueing system. This paper consists of Part I and II. In Part I, we present a (LRD) video traffic model based on the shifting-level (SL) process. We observe that the ACF of an empirical video trace is accurately captured by the shifting-level process with compound correlation (SLCC): an exponential function in short range and a hyperbolic function in long range. We present an accurate parameter matching algorithm for video traffic. In the Part II, we offer the queueing analysis of SL/D/1/K called ‘quantization reduction method’. Comparing the queueing performances of the DAR(1) model and the SLCC with that of a real video trace, we identify the effects of SRD and LRD in VBR video traffic on queueing performance. Simulation results show that Markoivian models can estimate network performances fairly accurately under a moderate traffic load and buffer condition, whereas LRD may have a significant effect on queueing behavior under a heavy traffic load and large buffer condition.

• Proceedings of the IEEK Conference
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• 2001.09a
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• pp.535-538
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• 2001

In this paper, we present a novel method to solve the inevitable RGB beam mismatch problem in projection TV receivers. Conventional methods solve the mismatch problem by directly controlling the cathode ray tube (CRT) using the convergence yoke (CY). Unlike conventional methods, the proposed method is based on digital video processing using image warping techniques. Firstly RGB beam projection paths are mathematically modeled. Then based on the modeling, the input video signal to CRT is prewarped so that RGB beams are landed at the same point on the screen. Since the proposed method is based on a digital video processing instead of using CY, it can outperform the conventional method in terms of quality and cost. The experimental results with a real 60´projection TV demonstrate that the proposed method indeed produces converged images on the projection TV screen.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.8
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• pp.623-628
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• 2000

Video-on-demand system in which users can request any video through the network at any time is made possible by rapid increase in network bandwidth and capacity of the media server. However true video-on-demand system cannot support all requests since bandwidth requirement is still too demanding. Therefore efficient bandwidth reduction algorithm is necessary. both the piggybacking method and the batching method are novel solutions that can provide more logical number of streams than the physical system can support. Of course each of them has its pros and cons. hence piggybacking with batching-by-size can take advantage of both the schemes. Some parameters such as the size of batch and the size of the catch-up window should be adjusted and order to maximize the bandwidth reduction for piggybacking with batching-by-size method. One of the most important parameters is decided optimally in this paper. Simulation shows that the optimized parameter can achieve considerable reductionand consequently remarkable enhancement in performance.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.2
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• pp.277-282
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• 2005

The arrangement of I-picture starting times of multiplexed variable bit .ate (VBR) MPEG videos may significantly affect the cell loss ratio (CLR) characteristics of the multiplexed traffic. This paper presents an efficient I-picture arrangement method which can minimize the CLR of the multiplexed traffic when multiple VBR MPEG videos are multiplexed onto a single constant bit rate link. In the proposed method, we use the probability that the arrival rate exceeds the link capacity as the measure for the CLR of the multiplexed traffic. Simulation results show that the proposed method can find more optimal arrangement than existing methods in respect of the CLR.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.11
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• pp.2465-2473
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• 2012

Recently, as one of low complexity video encoding methods, DVC (Distributed Video Coding) scheme has been actively studied. Most of DVC schemes exploit feedback channel to achieve better coding performances, however, this causes these schemes to have high decoding delay. In order to overcome these, this paper proposes a new fast DVC decoding method using parity-bit request model, which can be obtained by using bit-error rate, sent by encoder with motion vector, which is transmitted through feedback channel by decoder after generating side information. Through several simulations, it is shown that the proposed method improves greatly the decoding speed, compared to the conventional schemes.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.1
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• pp.69-76
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• 2010

The segmentation of moving object in video sequence is a core technique of intelligent image processing system such as video surveillance, traffic monitoring and human tracking. A typical method to segment a moving region from the background is the background subtraction. The steps of background subtraction involve calculating a reference image, subtracting new frame from reference image and then thresholding the subtracted result. One of famous background modeling is Gaussian mixture model (GMM). Even though the method is known efficient and exact, GMM suffers from a problem that includes false pixels in ROI (region of interest), specifically shadow pixels. These false pixels cause fail of the post-processing tasks such as tracking and object recognition. This paper presents a method for removing false pixels included in ROT. First, we subdivide a ROI by using shape characteristics of detected objects. Then, a method is proposed to classify pixels from using histogram characteristic and comparing difference of energy that converts the color value of pixel into grayscale value, in order to estimate whether the pixels belong to moving object area or shadow area. The method is applied to real video sequence and the performance is verified.