• Journal of Korea Multimedia Society
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• v.20 no.2
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• pp.196-204
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• 2017

Behavior of intelligent video surveillance system is recognized by analyzing the pattern of the object of interest by using the frame information of video inputted from the camera and analyzes the behavior. Detection of object's certain behaviors in the crowd has become a critical problem because in the event of terror strikes. Recognition of object's certain behaviors is an important but difficult problem in the area of computer vision. As the realization of big data utilizing machine learning, data mining techniques, the amount of video through the CCTV, Smart-phone and Drone's video has increased dramatically. In this paper, we propose a multiple-sliding window method to recognize the cumulative change as one piece in order to improve the accuracy of the recognition. The experimental results demonstrated the method was robust and efficient learning units in the classification of certain behaviors.

• Smart Structures and Systems
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• v.12 no.1
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• pp.73-95
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• 2013

Nine deoxyribonucleic acid (DNA) sequences were used to functionalize single-walled carbon nanotube (SWNT) sensors to detect the trace amount of methanol, acetone, and HCl in vapor. DNA 24 Ma (24 randomly arranged nitrogenous bases with one amine at each end of it) decorated SWNT sensor and DNA 24 A (only adenine (A) base with a length of 24) decorated SWNT sensor have demonstrated the largest sensing responses towards acetone and HCl, respectively. On the other hand, for the DNA GT decorated SWNT sensors with different sequence lengths, the optimum DNA sequence length for acetone and HCl sensing is 32 and 8, separately. The detection of methanol, acetone, and HCl have identified that DNA functionalized SWNT sensors exhibit great selectivity, sensitivity, and repeatability with an accuracy of more than 90%. Further, a sensor array composed of SWNT functionalized with various DNA sequences was utilized to identify acetone and HCl through pattern recognition. The sensor array is a combination of four different DNA functionalized SWNT sensors and two bare SWNT sensors (work as reference). This wireless sensing system has enabled real-time gas monitoring and air quality assurance for safety and security.

• IEIE Transactions on Smart Processing and Computing
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• v.4 no.1
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• pp.1-9
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• 2015

Template matching is used for many applications in image processing. One of the most researched topics is object tracking. Normalized Cross Correlation (NCC) is the basic statistical approach to match images. NCC is used for template matching or pattern recognition. A template can be considered from a reference image, and an image from a scene can be considered as a source image. The objective is to establish the correspondence between the reference and source images. The matching gives a measure of the degree of similarity between the image and the template. A problem with NCC is its high computational cost and occasional mismatching. To deal with this problem, this paper presents an algorithm based on the Sum of Squared Difference (SSD) and an adaptive template matching to enhance the quality of the template matching in object tracking. The SSD provides low computational cost, while the adaptive template matching increases the accuracy matching. The experimental results showed that the proposed algorithm is quite efficient for image matching. The effectiveness of this method is demonstrated by several situations in the results section.

• The KIPS Transactions:PartA
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• v.16A no.3
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• pp.209-216
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• 2009

The ubiquitous smart home is the home of the future that takes advantage of context information from the human and the home environment and provides an automatic home service for the human. Human location and motion are the most important contexts in the ubiquitous smart home. We present a real-time human tracker that predicts human location and motion for the ubiquitous smart home. We used four network cameras for real-time human tracking. This paper explains the real-time human tracker's architecture, and presents an algorithm with the details of two functions (prediction of human location and motion) in the real-time human tracker. The human location uses three kinds of background images (IMAGE1: empty room image, IMAGE2: image with furniture and home appliances in the home, IMAGE3: image with IMAGE2 and the human). The real-time human tracker decides whether the human is included with which furniture (or home appliance) through an analysis of three images, and predicts human motion using a support vector machine. A performance experiment of the human's location, which uses three images, took an average of 0.037 seconds. The SVM's feature of human's motion recognition is decided from pixel number by array line of the moving object. We evaluated each motion 1000 times. The average accuracy of all the motions was found to be 86.5%.

• The Journal of the Korea Contents Association
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• v.17 no.2
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• pp.96-104
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• 2017

As new smart devices are evolved into the intelligent agent who can reflect user intention and use context, user experience design for easy and convenient usability becomes a core competitive edge. Under the assumption that human centered natural interaction is necessary for the optimal smart TV experience, this study explores the types of voice interaction which are peculiar to TV watching context. In order to build a model for the users to naturally interact with Smart TV, conversation patterns were collected by requesting key features of Smart TV to intelligent agent. Collected sentences were applied to CfA model and classified by responses to activate features. The classified conversation patterns were divided into feature activation and information search. This study has identified that CfC1 occurred when voice interaction between Smart TV and users was vague and CfC2 occurred when the requests were complex or conditional. In conclusion, Simple Request Type is the most efficient model and voice interaction is more appropriate to use to clarify users' vague requests.

• Proceedings of the Korean Society of Computer Information Conference
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• 2013.07a
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• pp.61-64
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• 2013

본 논문에서는 모바일 기반 OpenCV 라이브러리를 이용한 마커리스 객체 인석 성능 향상을 위한 소프트웨어적인 관점의 방법을 제안한다. 기존의 마커리스 기반 알고리즘을 이용하여 테스트를 수행한 후 성능에 저하를 발생시키는 요인들을 분석하고 그에 따른 상황별 적절한 해결책을 제시한다. 이에 따라 크게 프로그램 코드 개선, 마커리스 기반 알고리즘 코드 개선, 센서를 활용한 성능 향상을 도모한다. 프로그램 코드 개선은 테스트 결과를 분석 한 후 수행시간이 가장 많이 소요되는 함수를 최적화하고 또한 최적의 특징점의 수를 제한한다. 마커리스 기반 알고리즘 코드 개선은 병렬 처리가 제공되는 모바일에 한하여 병렬처리기법으로 코드를 수정한다. 마지막 센서를 활용한 성능향상은 실시간 작업 처리 단위를 묶음으로 처리하였을 때 발생하는 품질의 저하를 보정하는 역할을 수행한다. 본 논문에서는 이러한 마커리스 객체 인식 성능 향상 방법을 소프트웨어적인 관점에서 제안하고 이에 대한 결과 모바일 기반 실시간 증강현실 서비스를 위한 성능 향상 면에서 효과적이다.

• IEIE Transactions on Smart Processing and Computing
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• v.4 no.4
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• pp.237-250
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• 2015

This paper describes a hardware-oriented algorithm and its conceptual implementation in a real-time speed limit traffic sign detection system on an automotive-oriented field-programmable gate array (FPGA). It solves the training and color dependence problems found in other research, which saw reduced recognition accuracy under unlearned conditions when color has changed. The algorithm is applicable to various platforms, such as color or grayscale cameras, high-resolution (4K) or low-resolution (VGA) cameras, and high-end or low-end FPGAs. It is also robust under various conditions, such as daytime, night time, and on rainy nights, and is adaptable to various countries' speed limit traffic sign systems. The speed limit traffic sign candidates on each grayscale video frame are detected through two simple computational stages using global luminosity and local pixel direction. Pipeline implementation using results-sharing on overlap, application of a RAM-based shift register, and optimization of scan window sizes results in a small but high-performance implementation. The proposed system matches the processing speed requirement for a 60 fps system. The speed limit traffic sign recognition system achieves better than 98% accuracy in detection and recognition, even under difficult conditions such as rainy nights, and is implementable on the low-end, low-cost Xilinx Zynq automotive Z7020 FPGA.

• Journal of the Korea Society of Computer and Information
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• v.16 no.6
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• pp.155-164
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• 2011

APP based on the smart phone is being utilized to various scopes such as medical services in hospitals, financing services at banks and credit card companies, and ubiquitous technologies in companies and homes etc. In this service environment, exposures of smart phones cause loss of assets including leaks of official/private information by outsiders. Though secret keys, pattern recognition technologies, and single image authentication techniques are being applied as protective methods, but they have problems in that accesses are possible by utilizing static key values or images like pictures. Therefore, this study proposes a face authentication technology for protecting smart phones from these dangerous factors and problems. The proposed technology authenticates users by extracting key frames of user's facial images by real time, and also controls accesses to the smart phone. Authentication information is composed of multiple key frames, and the user' access is controlled by distinction algorism of similarity utilizing DC values of image's pixel and luminance.

• Journal of Digital Convergence
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• v.16 no.10
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• pp.213-222
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• 2018

This study was conducted to derive the traffic accident risk index through the recognition of the elderly driver's driving pattern to reduce the traffic accident rate of elderly drivers and to reflect them in the renewal and return policy of driver's license accordingly. First, the traffic accident risk index is defined by analyzing the behavioral characteristics of older drivers to derive the major factors that lead to traffic accidents. Second, we present a method to measure the traffic accident risk index from the driving pattern of the elderly through the smart-phone, the camera and the distance sensor attached to the car. Finally, we derive three thresholds by computer simulation and determine the accident risk from the measured traffic accident risk index as four steps and suggest ways to ensure safe driving of older drivers. It is required to objectively assess the driving ability of an aged driver in accordance with the proposed method, and to induce the driver to reset the driver's license renewal cycle and voluntarily return the driver's license to minimize social costs due to increased traffic accidents.

• Journal of the Korean Institute of Intelligent Systems
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• v.27 no.2
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• pp.138-143
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• 2017

The purpose of this paper is to implement a smart touch image output system based on ICT. The image output system here uses a pen-touch type screen coordinate recognition type to minimize the error because there is a difference in the resolution of the motion pattern between the image screen and the actual image using the image sensing reaction sensor. To do so, we built a smart image output system that can output image data by using ICT based technology and can be operated remotely without a PC, laptop, monitor, keyboard and mouse by using wireless method and smart touch function instead of the existing wired method. The result of this study is that the image can be output only if there is a wall, and the pen can be operated on the output image without the screen.