• Korean Journal of Cognitive Science
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• v.13 no.2
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• pp.37-45
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• 2002

Despite dynamical retinal image changes caused by pursuit eye movements, we usually perceive the stable spatial properties of the environment suite successfully Helmholtz and his followers have suggested that the visual system coordinates the retinal and extraretinal eye position information to represent the spatial properties of the environment. However. there have been a significant amount of researches showing that this kind of mechanism may not operate perfectly, and the pursuit eye movement employed in those researches were limited to conjugate eye movements. When an observer tracks an object moving away from the observer with his/her eyes. the two eyes rotate in opposite direction. and this kind of disjunctive eye movement may produce undesirable binocular disparities for the objects in the background. The present study examined whether the visual system compensated for the undesirable binocular disparities caused by disjunctive eye movements with extraretinal eye position information. Although the target object was presented frontoparellely to the subjects. the subjects reported that the object was slanted toward (or alway from) them in consistent with the undesirable binocular disparities produced by the disjunctive eye movements. These results imply that the visual system may not perfectly compensate for the undesirable binocular disparities with extraretinal eye position information.

• Journal of the Korea Society of Computer and Information
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• v.20 no.5
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• pp.21-29
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• 2015

This paper proposes a shot change detection algorithm by using frame segmentation and the object changes among moving blocks. In order to detect the rapid moving changes of objects between two consecutive frames, the moving blocks on the diagonal are defined, and their histograms are calculated. When a block of the current frame is compared to the moving blocks of the next frame, the block histograms are used and the threshold of a shot change detection is automatically adjusted by Otsu's threshold method. The proposed algorithm was tested for the various types of color or gray videos such as films, dramas, animations, and video tapes in National Archives of Korea. The experimental results showed that the proposed algorithm could enhance the detection rate when compared to the studied methods that use brightness, histogram, or segmentation.

• The KIPS Transactions:PartD
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• v.11D no.1
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• pp.69-82
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• 2004

A moving object has a special feature that it's spatial location, shape and size are changed as time goes. These changes of the object accompany the continuous movement that is called the trajectory. In this paper, we propose an index structure that users can retrieve the trajectory of a moving object with the access of a page. We also propose the multi-complex query that is a new query type for trajectory retrieval. In order to prove the excellence of our method, we compare and analyze the performance for query time and storage space through experiments in various environments. It is shown that our method outperforms the existing index structures when processing spatio-temporal trajectory queries on moving objects.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.10a
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• pp.894-897
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• 2012

We propose a effective method using the HOG (Histogram of Oriented Gradients) feature vector to track individual objects in an environment which multiple objects are moving. The proposed algorithm consists of pre-processing, object detection and object tracking. We experimented with six videos which have various trajectories and the movement. When occlusion between objects was occurred, we identified individual object by using center and predicted coordinates of moving objects. The algorithm shows 85.45% of tracking rate in the videos we experimented. We expect the proposed system is utilized in security systems which require the alalysis of the position and motion pattern of objects.

• Journal of the Korea Society of Computer and Information
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• v.13 no.6
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• pp.1-12
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• 2008

This paper presents automatic moving object detection method using the rotating camera covering larger area with a single camera. The proposed method is based on the edge segment matching which robust to the dynamic environment with illumination change and background movement. The proposed algorithm presents an edge segment based background panorama image generation method minimizing the distortion due to image stitching, the background image generation method using Generalized Hough Transformation which can reliably register the current image to the panorama image overcoming the stitching distortions, the moving edge segment extraction method that overcome viewpoint difference and distortion. The experimental results show that the proposed method can detect correctly moving object under illumination change and camera vibration.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.11C
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• pp.1551-1563
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• 2004

This paper proposes a hierarchical approach to shape model ASM using wavelet transform. Local structure model fitting in the ASM plays an important role in model-based pose and shape analysis. The proposed algorithm can robustly find good solutions in complex images by using wavelet decomposition. we also proposed effective method that estimates and corrects object's movement by using Wavelet transform-based hierarchical motion estimation scheme for ASM-based, real-time video tracking. The proposed algorithm has been tested for various sequences containing human motion to demonstrate the improved performance of the proposed object tracking.

• Journal of information and communication convergence engineering
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• v.21 no.3
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• pp.252-260
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• 2023

A bullet launcher can be developed as a smart instrument, especially for use in the military section, that can track, identify, detect, mark, lock, and shoot a target by implementing an image-processing system. In this research, the application of object recognition system, laser encoding as a unique marker, 2-dimensional movement, and pneumatic as a shooter has been studied intensively. The results showed that object recognition system could detect various colors, patterns, sizes, and laser blinking. Measuring the average error value of the object distance by using the camera is ±4, ±5, and ±6% for circle, square and triangle form respectively. Meanwhile, the average accuracy of shots on objects is 95.24% and 85.71% in indoor and outdoor conditions respectively. Here, the average prototype response time is 1.11 s. Moreover, the highest accuracy rate of shooting results at 50 cm was obtained 98.32%.

• Journal of Digital Convergence
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• v.10 no.6
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• pp.297-302
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• 2012

In this paper, we present a object detection and tracking method based on image context analysis. It is robust from the image variations such as complicated background, dynamic movement of the object. Image context analysis is carried out using the hybrid network of k-means and RBF. The proposed object detection employs context-driven adaptive Bayesian framework to relive the effect due to uneven object images. The proposed method used feature vector generator using 2D Haar wavelet transform and the Bayesian discriminant method in order to enhance the speed of learning. The system took less time to learn, and learning in a wide variety of data showed consistent results. After we developed the proposed method was applied to real-world environment. As a result, in the case of the object to detect pass outside expected area or other changes in the uncertain reaction showed that stable. The experimental results show that the proposed approach can achieve superior performance using various data sets to previously methods.

• Journal of Science of Art and Design
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• v.12
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• pp.125-143
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• 2007

The politics penetrating through the contemporary art since modernism to postmodernism is to accomplish the 'Non-representation' in the artworks. This study argues that postmodernism did not put an end to the formalistic feature of modernism but intended to accomplish it. Modernist art aimed at purity, i.e. self-referential and self-definition art advocated by Clement Greenberg, and it carne to the end by accomplishing flatness and materiality. It was an 'evasion to the matter' which allocated the object from visuality of outer object to the psychic image of the subject. It failed being 'non-representational' as what it really achieved was transition of object. Jean Baudrillard's theory tried to overcome the representational quality by 'being simulacre'. In the representative artworks of the past, the meaning of artworks was reverted under the outer context or object. The meaning again failed being 'Non-representational' as it was restored to the psychic image of the subject in modernist artworks where the definite illusion was demolished Meanwhile, artwork advocating simulacre acquired Non-representational quality by liberating from both models. It did not deconstruct the self-referential tendency of modernism but maximized the Non-representational modernistic principle. After creating 'Non-representation' through simulacre, the existential status and function of an artwork is the inclination and moral of contemporary art as 'Non-representation'. The image theory of Henri Bergson sets the existential status of 'image' as it does not belong to either subject nor object. It provides significant foundation for arguing the existential status of simulacre. Moreover, though an artwork as a fragment forming a movement image in the world cannot represent the object, it can however sustain certain kind of fractal resemblance with the world by letting the two parties communicate. The theory of sense by Gilles Deleuze is of profound significance as it specifically indicated way how the stage of absorption through the unity of subject and object is realized in forms of artworks, and configured the latent and invisible energy.

• Journal of Advanced Navigation Technology
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• v.16 no.2
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• pp.386-393
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• 2012

In this paper, we propose an efficient multi-object recognition and tracking scheme based on interest points of objects and their feature descriptors. To do that, we first define a set of object types of interest and collect their sample images. For sample images, we detect interest points and construct their feature descriptors using SURF. Next, we perform a statistical analysis of the local features to select representative points among them. Intuitively, the representative points of an object are the interest points that best characterize the object. in addition, we make the movement vectors of the interest points based on matching between their SURF descriptors and track the object using these vectors. Since our scheme treats all the objects independently, it can recognize and track multiple objects simultaneously. Through the experiments, we show that our proposed scheme can achieve reasonable performance.