• Journal of information and communication convergence engineering
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• v.9 no.2
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• pp.201-206
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• 2011

FRUC (Frame Rate Up-Conversion) technique needs an effective frame interpolation algorithm using motion information between adjacent neighboring frames. In order to have good visual qualities in the interpolated frames, it is necessary to develop an effective detection and interpolation algorithms for occluded regions. For this aim, this paper proposes an effective occluded region detection algorithm through the adaptive forward and backward motion searches and also by introducing the minimum value of normalized cross-correlation coefficient (NCCC). That is, the proposed scheme looks for the location with the minimum sum of absolute differences (SAD) and this value is compared to that of the location with the maximum value of NCCC based on the statistics of those relations. And, these results are compared with the size of motion vector and then the proposed algorithm decides whether the given block is the occluded region or not. Furthermore, once the occluded regions are classified, then this paper proposes an adaptive interpolation algorithm for occluded regions, which still exist in the merged frame, by using the neighboring pixel information and the available data in the occluded block. Computer simulations show that the proposed algorithm can effectively classify the occluded region, compared to the conventional SAD-based method and the performance of the proposed interpolation algorithm has better PSNR than the conventional algorithms.

• Journal of the Korea Society of Computer and Information
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• v.17 no.1
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• pp.97-104
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• 2012

Natural User Interface(NUI) technologies introduce new trends in using devices such as computer and any other electronic devices. In this paper, an augmented reality on a mobile device is implemented by using face detection, recognition and motion tracking. The face detection is obtained by using Viola-Jones algorithm from the images of the front camera. The Eigenface algorithm is employed for face recognition and face motion tracking. The augmented reality is implemented by overlapping the rear camera image and GPS, accelerator sensors' data with the 3D graphic object which is correspond with the recognized face. The algorithms and methods are limited by the mobile device specification such as processing ability and main memory capacity.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.5 s.305
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• pp.79-84
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• 2005

In this paper, we developed an omni-directional surveillance and motion detection method. The fish-eye lens provides a wide field of view image. Using this image, the equi-distance model for the fish-eye lens is applied to get the perspective and panorama images. Generally, we must consider the trade-off between resolution and field of view of an image from a camera. To enhance the resolution of the result images, some kind of interpolation methods are applied. Also the moving edge method is used to detect moving objects for the object tracking.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.4
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• pp.903-910
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• 2018

The necessary rehabilitation training for patients with disability currently does not match the actual amount of training conducted, which requires interest in rehabilitation treatment, continued investment and infrastructure for rehabilitation contents, while the most common forms of rehabilitation treatment comprises of art, music, and play treatments. In this paper, we provide a game-style rehabilitation program including audio and visual elements through motion detection process on the patient and design a digital game rehabilitation program that allows different level of management for various categories of disabled people.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.860-863
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• 2010

Wireless sensor networks consist of small, autonomous devices with wireless networking capabilities. In order to further increase the applicability in real world applications, minimizing energy consumption is one of the most critical issues. Therefore, accurate energy model is required for the evaluation of wireless sensor networks. In this paper, we analyze the energy consumption for wireless sensor networks. To estimate the lifetime of sensor node, we have measured the energy characteristics of sensor node based on Telosb platforms running TinyOS. Based on the proposed model, the estimated lifetime of a battery powered sensor node can use about 6.925 months for 10 times motion detection per hour.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.10
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• pp.5074-5094
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• 2016

Screen splitting is one of the fundamental tasks in different methods including video and image compression, screen classification, screen content coding and the like. These methods in turn support various applications in data communications, remote screen sharing, remote desktop delivery to assist teaching-learning, telemedicine, Desktop as a Service etc. In the literature we find systems requiring splitting assumes a fixed size split that do not change dynamically, also there is no analysis why that split is chosen in terms of performance. By doing mathematical analysis this paper first finds the efficient splitting schemes that can be easily automated to make a system adaptive. Thereafter, taking the screen motion detection as a case study, it demonstrates the effects of various splitting methods on motion detection performance. The simulation results clearly shows how classification performances varies with different splitting which will facilitate to choose the best splitting for a specific application scenario as well as making the system adaptive by providing dynamic splitting.

• International Journal of Contents
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• v.4 no.2
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• pp.24-28
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• 2008

In this paper, we propose a new approach for content-based video retrieval using non-parametric based motion classification in the shot-based video indexing structure. Our system proposed in this paper has supported the real-time video retrieval using spatio-temporal feature comparison by measuring the similarity between visual features and between motion features, respectively, after extracting representative frame and non-parametric motion information from shot-based video clips segmented by scene change detection method. The extraction of non-parametric based motion features, after the normalized motion vectors are created from an MPEG-compressed stream, is effectively fulfilled by discretizing each normalized motion vector into various angle bins, and by considering the mean, variance, and direction of motion vectors in these bins. To obtain visual feature in representative frame, we use the edge-based spatial descriptor. Experimental results show that our approach is superior to conventional methods with regard to the performance for video indexing and retrieval.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.1735-1736
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• 2008

In this research, a riding robot system named as "RideBot" is developed for health-care and entertainments. The developed riding robot can follow the intention of horseman and can simulate the motion of horse. The riding robot mechanisms are used for many functions of attitude detection, motion sensing, recognition, common interface and motion-generations. This riding robot can react on health conditions, bio-signals and intention informations of user. One of the objectives of this research is that the riding robot could catch user motion and operate spontaneous movements. In this paper, we develope the saddle mechanism which can generate 3 degrees-of-freedom riding motion based on the intention of horseman. Also, we develope reins and spur mechanism for the recognition of the horseman's intention estimation and the bio-signal monitoring system for the health care function of a horseman. In order to evaluate the performance of the riding robot system, we tested several riding motions including slow and normal step motion, left and right turn motion.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.321-323
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• 2015

Monitoring crane motion in real time is the first step to identifying and mitigating crane-related hazards on construction sites. However, no accurate and reliable crane motion capturing technique is available to serve this purpose. The objective of this research is to explore a method for real-time crane motion capturing and investigate an approach for assisting hazard detection. To achieve this goal, this research employed various techniques including: 1) a sensor-based method that accurately, reliably, and comprehensively captures crane motions in real-time; 2) computationally efficient algorithms for fusing and processing sensing data (e.g., distance, angle, acceleration) from different types of sensors; 3) an approach that integrates crane motion data with known as-is environment data to detect hazards associated with lifting tasks; and 4) a strategy that effectively presents crane operator with crane motion information and warn them with potential hazards. A prototype system was developed and tested on a real crane in a field environment. The results show that the system is able to continuously and accurately monitor crane motion in real-time.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.1
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• pp.35-41
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• 2012

This paper proposes a moving object detection algorithm for active camera system that can be applied to mobile robot and intelligent surveillance system. Most of moving object detection algorithms based on a stationary camera system. These algorithms used fixed surveillance system that does not consider the motion of the background or robot tracking system that track pre-learned object. Unlike the stationary camera system, the active camera system has a problem that is difficult to extract the moving object due to the error occurred by the movement of camera. In order to overcome this problem, the motion of the camera was compensated by using SURF and Pseudo Perspective model, and then the moving object is extracted efficiently using stochastic Label Cluster transport model. This method is possible to detect moving object because that minimizes effect of the background movement. Our approach proves robust and effective in terms of moving object detection in active camera system.