Il-Ju Ko

Intelligent copyright protection system using a matching video retrieval algorithm

Many video service sites headed by YouTube know what content requires copyright protection. However, they lack a copyright protection system that automatically distinguishes whether uploaded videos contain legal or illegal content. Existing protection techniques use content-based retrieval methods that compare the features of video. However, if the video encoding has changed in resolution, bit-rate or codec, these techniques do not perform well. Thus, this paper proposes a novel video matching algorithm even if the type of encoding has changed. We also suggest an intelligent copyright protection system using the proposed algorithm. This can serve to automatically prevent the uploading of illegal content. The proposed method has represented the accuracy of 97% with searching algorithm in video-matching experiments and 98.62% with automation algorithm in copyright-protection experiments. Therefore, this system could form a core technology that identifies illegal content and automatically excludes access to illegal content by many video service sites.

An algorithm that minimizes audio fingerprints using the difference of Gaussians

Recently, many audio search sites headed by Google have used audio fingerprinting technology to search for the same audio and protect the music copyright using one part of the audio data. However, if there are fingerprints per audio file, then the amount of query data for the audio search increases. In this paper, we propose a novel method that can reduce the number of fingerprints while providing a level of performance similar to that of existing methods. The proposed method uses the difference of Gaussians which is often used in feature extraction during image signal processing. In the experiment, we use the proposed method and dynamic time warping and undertake an experimental search for the same audio with a success rate of 90%. The proposed method, therefore, can be used for an effective audio search.

Identical-video retrieval using the low-peak feature of a video’s audio information

The recognition and retrieval of identical videos by combing through entire video files requires a great deal of time and memory space. Therefore, most current video-matching methods analyze only a part of each video’s image frame information. All these methods, however, share the critical problem of erroneously categorizing identical videos as different if they have merely been altered in resolution or converted with a different codec. This paper deals instead with an identical-video-retrieval method using the low-peak feature of audio data. The low-peak feature remains relatively stable even with changes in bit-rate or codec. The proposed method showed a search success rate of 93.7% in a video matching experiment. This approach could provide a technique for recognizing identical content on video file share sites.

Inference of recommendation information on the internet using improved FAM

This paper proposes a collaborative filtering system using Improved Fuzzy Associative Memory (IFAM) which readjusts the connection weights between the nodes of FAM using error back propagation and simplifies the Fuzzy rules. The proposed technique automatically recommends high-quality information to users with similar interests on arbitrarily narrow information domains. It asks a user to rate a gauge set of items. It then evaluates the users rates and suggests a recommendation set of items. The proposed system is implemented in a web server and tested its performance in the domain of retrieval of technical papers, especially in the field of information technologies. The experimental results show that it may piovide reliable recommendations.

A climbing motion recognition method using anatomical information for screen climbing games

Screen climbing games have made a new category of gaming experience between a human climber and a virtual game projected onto an artificial climbing wall. Here, climbing motion recognition is required to interact with the game. In existing climbing games, motion recognition is based on a simple calculation using the depth difference between the climber’s body area and the climbing wall. However, using the body area in this way is devoid of anatomical information; thus the gaming system cannot recognize which part, or parts, of the climber’s body is in contact with the artificial climbing wall. In this paper, we present a climbing motion recognition method using anatomical information obtained by parsing a climber’s body area into its constituent anatomical parts. In ensuring that game events consider anatomical information, a climbing game can provide a more immersive experience for gamers.

Data-Sharing Method for Multi-Smart Devices at Close Range

We proposed a useful data-sharing method among multi-smart devices at close range using inaudible frequencies and Wi-Fi. The existing near data-sharing methods mostly use Bluetooth technology, but these methods have the problem of being unable to be operated using different operating systems. To correct this flaw, the proposed method that uses inaudible frequencies through the inner speaker and microphone of smart device can solve the problems of the existing methods. Using the proposed method, the sending device generates trigger signals composed of inaudible sound. Moreover, smart devices that receive the signals obtain the shared data from the sending device through Wi-Fi. To evaluate the efficacy of the proposed method, we developed a near data-sharing application based on the trigger signals and conducted a performance evaluation experiment. The success rate of the proposed method was 98.8%. Furthermore, we tested the user usability of the Bump application and the proposed method and found that the proposed method is more useful than Bump. Therefore, the proposed method is an effective approach for sharing data practically among multi-smart devices at close range.

Realtime 3D Stereoscopic Image based on Single Camera with Marker Recognition

However, in order to create a stereoscopic 3D image, independently, it is required to spend expensive manufacturing costs and to have special techniques. As 3D display devices have been generalized, there is an increasing need for implementing a stereoscopic 3D image without a burden of expensive costs. This paper proposes some methods to implement stereoscopic 3D images easily by utilizing a marker tracking technology using a single camera. In addition, the study made it possible for the resolution of an image to be adjustable dynamically. This paper will be committed to the promotion of the field of UCC (User Created Contents) using stereoscopic 3D images by attracting the active participation of general users in the field of the implementation of stereoscopic 3D images.

A frame-based model for hand gesture recognition

In this paper, we present a home-based model for hand gesture recognition. We define two different types of frames, object frames and behavior frames, and integrate them into schemas to model meaningful hand gestures. A schema specifies in what order object frames and behavior frames have to be evoked. One of our design goals is to provide a framework which virtually imposes no restrictions on the type of hand gestures it can handle, so that the system can be easily adapted to particular applications.

Detection of a Robust High-Frequency Range via Noise Analysis in a Real-World Environment

Recently, many studies have been conducted on using inaudible high frequencies for wireless communication based on smart devices and data transmission algorithms. However, many studies have identified a problem such that transmission accuracy is extremely low because of ambient noise in the real-life environment. To solve this problem, we proposed an application and server system. The proposed application can gather many sounds, including those with high frequencies; the gathered high frequencies are sent to a server system that can detect a robust high-frequency range via statistical processing. We tested the proposed application’s ability to gather noise and high frequencies for a certain period of time to evaluate performance. According to the testing results, the proposed application and server system could detect a robust high-frequency range via noise analysis in real life. Therefore, the proposed application and server could be a useful technology for future research on inaudible high frequencies.

Analysis of Game Character Using Emotion Rule

ABSTRACT Emotion is one of the elements of the game that will help the user interaction. The way to express the emotions and personality of the character was taken into account severity of reaction to action or a specific graphics in the game so far. However recently structured for the interest in the study of emotion increases and to utilize a variety of feelings in the game is needed. In the field of autonomous agents, studies of the possibility of the use of emotion, defined 12 different emotion rules. In this paper, we dilate by defining the terms used in the game rules of emotion made ​the rules of the emotion of the game. And, we analyzed emotions in actual game character used Game Emotions Rule. As a result, it was possible to see the rules of the game feeling separate from that being used for game genre similar.Keywords : Game(게임), Emotion Rule(감정규칙), Character(캐릭터) Received: Dec. 16, 2013 Revised: Feb. 20, 2014Accepted: Mar. 10, 2014Corresponding Author: Il-Ju Ko(Soong-sil University)E-mail: andy1026@gmail.comISSN: 1598-4540 / eISSN: 2287-8211Ⓒ The Korea Game Society. All rights reserved. This is an open-access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.otg/licenses/by-nc/3.0), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.