• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2005.11a
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• pp.282-285
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• 2005

This paper discusses the interactive system for smart home environments. In order to realize this, the main emphasis of the paper lies on the description of the multiple signal processing on the basis of the technologies such as fingerprint recognition, video signal processing, speech recognition and synthesis. For essential modules of the interactive system, we adopted the motion detector based on the changes of brightness in pixels as well as the fingerprint identification for adapting home environments to the inhabitants. In addition, the real-time speech recognizer based on the HM-Net(Hidden Markov Network) and the speech synthesis were incorporated into the overall system for interaction between user and system. In experimental evaluation, the results showed that the proposed system was easy to use because the system was able to give special services for specific users in smart home environments, even though the performance of the speech recognizer was not better than the simulation results owing to the noisy environments.

• The Journal of the Korea Contents Association
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• v.10 no.12
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• pp.51-58
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• 2010

In the environment of instant messengers, the recognition of human emotions and its automated representation with personalized 3D character animations facilitate the use of affectivity in the machine-based communication, which will contribute to enhanced communication. This paper describes an emotional messenger system developed for the automated recognition and expression of emotions for IPTVs (Internet Protocol televisions). Aiming for efficient delivery of users' emotions, we propose emotion estimation that assesses the affective contents of given textual messages, character animation that supports both 3D rendering and video playback, and smart phone-based input method. Demonstration and experiments validate the usefulness and performance of the proposed system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.6
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• pp.2483-2503
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• 2016

Traffic congestion is a severe problem in many modern cities around the world. Real-time and accurate traffic congestion identification can provide the advanced traffic management systems with a reliable basis to take measurements. The most used data sources for traffic congestion are loop detector, GPS data, and video surveillance. Video based traffic monitoring systems have gained much attention due to their enormous advantages, such as low cost, flexibility to redesign the system and providing a rich information source for human understanding. In general, most existing video based systems for monitoring road traffic rely on stationary cameras and multiple vehicle tracking method. However, most commonly used multiple vehicle tracking methods are lack of effective track initiation schemes. Based on the motion of the vehicle usually obeys constant velocity model, a novel vehicle recognition method is proposed. The state of recognized vehicle is sent to the GM-PHD filter as birth target. In this way, we relieve the insensitive of GM-PHD filter for new entering vehicle. Combining with the advanced vehicle detection and data association techniques, this multiple vehicle tracking method is used to identify traffic congestion. It can be implemented in real-time with high accuracy and robustness. The advantages of our proposed method are validated on four real traffic data.

• Journal of the Korea Convergence Society
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• v.8 no.3
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• pp.15-22
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• 2017

People generally believe that disaster forecast and warning systems and response systems are well established in the age of cutting edge technology. As a matter of fact, reliable systems to respond to disasters are not properly equipped, as we witnessed the Sewol ferry disaster in 2014. The existing forecast and warning systems are based on sensor information with low efficiency, and image information is only operated by monitoring staff manually. In addition, the interconnection between a warning system and a response system in order to decide how to cope with the recognized disaster is very insufficient. This paper introduces the CCTV based disaster recognition and real time crisis response system composed of the CCTV image recognition engine and the crisis response technique. This system has brought the possibility to overcome the limitations of existing sensor based forecast and warning systems, and to resolve the problems in the absence of monitoring staff when responding to crisis.

• International Journal of Advanced Culture Technology
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• v.7 no.4
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• pp.289-294
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• 2019

As social network service platforms grow and one-person media market expands, people upload their own photos and/or videos through multiple open platforms. However, it can be illegal to upload the digital contents containing the faces of others on the public sites without their permission. Therefore, many people are spending much time and effort in editing such digital contents so that the faces of others should not be exposed to the public. In this paper, we propose an automatic face hiding system called 'autoblur', which detects all the unregistered faces and mosaic them automatically. The system has been implemented using the GitHub MIT open-source 'Face Recognition' which is based on deep learning technology. In this system, two dozens of face images of the user are taken from different angles to register his/her own face. Once the face of the user is learned and registered, the system detects all the other faces for the given photo or video and then blurs them out. Our experiments show that it produces quick and correct results for the sample photos.

• Journal of Korea Multimedia Society
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• v.20 no.1
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• pp.17-31
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• 2017

The aim of the paper is to present an object recognition method toward augmented reality system that utilizes existing education instruments that was designed without any consideration on image processing and recognition. The light reflection, sizes, shapes, and color range of the existing target education instruments are major hurdles to our object recognition. In addition, the real-time performance requirements on embedded devices and user experience constraints for children users are quite challenging issues to be solved for our image processing and object recognition approach. In order to meet these requirements we employed a method cascading light-weight weak classification methods that are complimentary each other to make a resultant complicated and highly accurate object classifier toward practically reasonable precision ratio. We implemented the proposed method and tested the performance by video with more than 11,700 frames of actual playing scenario. The experimental result showed 0.54% miss ratio and 1.35% false hit ratio.

• Journal of Korea Multimedia Society
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• v.10 no.1
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• pp.117-127
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• 2007

As the value of the multimedia data is getting high, the study on the semantic recognition and retrieval about the multimedia information is strongly demanded. In this paper, we build the motion ontology and adopt it for representing the meaning of the moving objects in video data. By referencing the WordNet structure, we extend its semantic meaning based on the reclassification of motion verbs, which are used to represent the semantic meaning of moving objects. The represented information is receded in OWL/RDF(S). Here, we could expect the 'Is-A' and 'Equivalent' reasoning of the data as we use the ontologies. And the semantic representation about the moving objects is possible through the video annotation using ontology. And we tested the accuracy of the system comparing with the key-word based system. As a result, we could get the approximately 10% improvement of the system performance.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.5 no.7
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• pp.1280-1286
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• 2001

In this Study, we try to suggest a system that recognize worker's regular motion more effectively First, based on frame difference that separates still background from movable object to video that make a film of worker's motion. The next, with edge detection, estimating the center of motion could recognize continuous motion. By action cognition system that design in this research films worker's action using fixed CCTV to supplement problem of action awareness system that is applied in existent industry spot, various mountings to get action information minimized. Also, shorten session that need in awareness enforcing action awareness through image subtraction and edge detection between frame to reduce time necessary to draw worker's body part special quality, expense designed inexpensive action cognition system as being efficient.

• 한국공간정보시스템학회:학술대회논문집
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• 2007.06a
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• pp.188-193
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• 2007

본 논문에서는 실사영상을 기반으로 동작하는 내비게이션에서 핵심적인 역할을 담당하고 있는 모듈 가운데 하나인 도로객체인식 모듈의 기능에 대해서 살펴보고자 한다. 이 모듈은 기존의 맵 기반의 내비게이션에서 찾아볼 수 없는 부분이며, 실사 영상위에 차량의 경로를 안내하기 위해서는 이 모듈을 통해 다양한 도로객체를 인식해야 하는데, 주행차선인식, 주행차로인식 및 신호등 인식이 필요하며 경우에 따라서는 건물인식이 여기에 포함될 수 있다.

• Annual Conference of KIPS
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• 2023.05a
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• pp.424-426
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• 2023

비디오 월 컨트롤러의 멀티스크린에 영상을 표출하기 위해서는 입력 영상과 영상의 수신 및 표출을 수행하는 클라이언트 프로그램이 필요하다. 입력 영상을 얻기 위한 수단으로는 영상 송출이 가능한 장비를 케이블로 연결하거나 네트워크를 통해 수신하는 방법이 있다. 많은 스트리밍 장치를 보유하고 있는 시스템에서는 관리가 용이한 영상분배서버를 사용하는 것이 효율적이지만, 통상의 영상분배 서버는 컴퓨터 비전 기술을 탑재하고 있지 않고 일단 스트리밍을 시작한 후에는 스트리밍 장치를 변경할 수 없는 단점이 있다. 이에 본 논문에서는 스트리밍을 실행한 후에도 스트리밍 장치를 전환하여 스트림을 전송할 수 있는 얼굴 인식 기반의 영상분배 시스템을 제안한다.