• Journal of Electrical Engineering and Technology
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• v.13 no.2
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• pp.961-968
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• 2018

Recently, researches on automatic recognition of human activities have been actively carried out with the emergence of various intelligent systems. Since a large amount of visual data can be secured through Closed Circuit Television, it is required to recognize human behavior in a dynamic situation rather than a static situation. In this paper, we propose new intelligent human activity recognition model using the trajectory information extracted from the video sequence. The proposed model consists of three steps: segmentation and partitioning of trajectory step, feature extraction step, and behavioral learning step. First, the entire trajectory is fuzzy partitioned according to the motion characteristics, and then temporal features and spatial features are extracted. Using the extracted features, four pedestrian behaviors were modeled by decision tree learning algorithm and performance evaluation was performed. The experiments in this paper were conducted using Caviar data sets. Experimental results show that trajectory provides good activity recognition accuracy by extracting instantaneous property and distinctive regional property.

• Journal of the Korean Society of Tobacco Science
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• v.19 no.1
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• pp.5-10
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• 1997

Three strains of W isolated from tobacco, tomato and Pepper plants in Korea were characterized based on biological response, serological relationship, and peptide mapping of the capsid Proteins. The strains designated as TMV-common, TMV-Pepper, and TMV-tomato could be distinguishable by different visual symptoms on 3 varieties of tobacco, one variety of tomato and Pepper for each among 27 plant specieces. Serological relationships were examined by agar gel double diffusion test. Only traceable or weak reaction was observed in the incompatible antigen-antibody combinations. The Pepper strain, however, showed trace in reaction with other two antisera. Peptide maps of the capsid proteins digested by V8 protease or by trypsin were also distinguishable, suggesting differences in composition and/or sequence of the amino acids among the strains.

• The Journal of Korea Robotics Society
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• v.1 no.2
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• pp.172-179
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• 2006

In this paper, we present a practical place and object recognition method for guiding visitors in building environments. Recognizing places or objects in real world can be a difficult problem due to motion blur and camera noise. In this work, we present a modeling method based on the bidirectional interaction between places and objects for simultaneous reinforcement for the robust recognition. The unification of visual context including scene context, object context, and temporal context is also. The proposed system has been tested to guide visitors in a large scale building environment (10 topological places, 80 3D objects).

• Journal of the Korea Society for Simulation
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• v.14 no.2
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• pp.25-34
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• 2005

Determination of component mounting sequence on printed circuit board assembly process is a typical NP-hard problem. It is a kind of traveling salesman problems, but it has one more hard to meet constraint of matching component type per mounting position as well as searching the shortest path. An efficient method is developed by separation of crowed area and allowing up to two slots per component type. A simulation model is constructed using Visual C++ for evaluation of the suggested heuristic.

• IEIE Transactions on Smart Processing and Computing
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• v.4 no.2
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• pp.110-114
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• 2015

This paper reports a novel object-detection technique in video sequences. The proposed algorithm consists of detection of objects in illuminated and occluded videos by using object features and a neural network technique. It consists of two functional modules: region-based object feature extraction and continuous detection of objects in video sequences with region features. This scheme is proposed as an enhancement of the Lowe's scale-invariant feature transform (SIFT) object detection method. This technique solved the high computation time problem of feature generation in the SIFT method. The improvement is achieved by region-based feature classification in the objects to be detected; optimal neural network-based feature reduction is presented in order to reduce the object region feature dataset with winner pixel estimation between the video frames of the video sequence. Simulation results show that the proposed scheme achieves better overall performance than other object detection techniques, and region-based feature detection is faster in comparison to other recent techniques.

• Proceedings of the Korean Institute of Interior Design Conference
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• 2001.05a
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• pp.90-94
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• 2001

This study hypothesizes that the imageability of a particular environments is decided by the unity of each visual sequences. We selected Ch'angdok Palace as our subject due to its greater applicability for image construction among various Korean architectures and their street furnitures. we apply the analytical methods of formal aesthetics and symbolic aesthetics to Ch'angdok Palace's space compositional characteristics, we can find distinctive features. The conclusions are that Ch'angdok Palace contains high probability of imageability through the contrast and harmony of two themes, reality and the ideal, and the rational and the emotional.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.7C
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• pp.540-547
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• 2008

In this paper, we proposed a new VLSI architecture which can generate computer-generated hologram (CGH) in real-time and implemented to hardware. The modified algorithm for high-performance CGH was introduced and re-analyzed (or designing hardware. from both numerical and visual analysis, the infernal number system of hardware was decided. CGH algorithm and precision analysis enabled to propose a new cell architecture for CGH. The operational sequence was analyzed with the architecture of CGH cell and the characteristics of the modified CGH algorithm, and finally the pipelined architecture and the operational timing were proposed.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.11
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• pp.935-940
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• 2002

For robot navigation and visual reconstruction, structure from motion (SFM) is an active issue in computer vision community and its properties arc also becoming well understood. In this paper, when using stereo image sequence and direct method as a tool for SFM, we present a new method for overcoming bas-relief ambiguity. We first show that the direct methods, based on optical flow constraint equation, are also intrinsically exposed to such ambiguity although they introduce robust methods. Therefore, regarding the motion and depth estimation by the robust and direct method as approximated ones. we suggest a method that refines both stereo displacement and motion displacement with sub-pixel accuracy, which is the central process f3r improving its ambiguity. Experiments with real image sequences have been executed and we show that the proposed algorithm has improved the estimation accuracy.

• Journal of Korea Multimedia Society
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• v.24 no.6
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• pp.796-804
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• 2021

In computer vision, visual tracking method addresses the problem of localizing an specific object in video sequence according to the bounding box. In this paper, we propose a tracking method by introducing the feature correlation comparison into the siamese network to increase its matching identification. We propose a way to compute location of object to improve matching performance by a correlation operation, which locates parts for solving the searching problem. The higher layer in the network can extract a lot of object information. The lower layer has many location information. To reduce error rate of the object center point, we built a siamese network that extracts the distribution and location information of target objects. As a result of the experiment, the average center error rate was less than 25%.

• Research in Mathematical Education
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• v.26 no.2
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• pp.105-120
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• 2023

With the rapid advancement of educational technology, recent studies have connected teachers' professional noticing with the use of digital resources in mathematical instructions. In this study, I examined elementary mathematics preservice teachers' attending and interpreting a mathematical software, ST Math, in the exploring and implementing phases. The findings indicate that preservice teachers paid attention to visual representations and manipulation prior to interactions with children and further took into consideration on task structures and situated context after interactions. They interpreted the events based on connected mathematical knowledge of prior interactions and further reflected on the progression of problem-solving strategies and sequence of tasks. In addition, four distinctive profiles of transitioning of evaluation on ST Math activities were identified with illustrations. Implications for noticing and teacher education were discussed.