• Journal of Digital Convergence
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• v.15 no.8
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• pp.333-340
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• 2017

Timelapse is an imaging technique that captures motion at regular intervals and then projects it at normal speed. We looked at Timelapse advertising images of global brands and presented a model for analyzing components and expression methods of Timelapse, a new image technique. In previous research, literature research, Internet data survey, and YouTube data were investigated. Continuous photography has been developed as an imaging technique, and we have examined the current production status applied to domestic and foreign documentary, domestic and foreign drama, film, and advertisement. In 2015-2016, I will analyze the techniques of iPhones (2016), Ralph Lauren Polo Ads (2015), and Canon EOS (2013) videos that use Timelapse techniques in their recent advertisements. The results show that the Timelapse component is a static element, the static motif is mainly an artificial structure, the place is outdoor, the color is taken at a time showing the characteristics of the place, and the layout is all centered. The dynamic motif is a moving object. The dynamic line consists of a story based on the object. The time is about 11-15 seconds, the longest is about 1 minute and 30 seconds, and the editing is mainly focused on the product with the brand logo emphasized. In conclusion, it is the role of the image to pay attention to the advertisement and catch the eye. In order to motivate the buyer's mind, it is necessary to direct and edit such as Timelapse, which stimulates the emotions inherent in the mind and stimulates the non-verbal symbols. Future research is likely to reveal various attempts at temporal editing of images.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.1
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• pp.141-148
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• 2011

Most of the previous works on scene change detection algorithm focus on the detection of abrupt rather than gradual changes. In general, gradual scene change detection algorithms require heavy computation. Some of those approaches don't consider the error factors such as flashlights, camera or object movements, and special effects. Many scenes change detection algorithms based on the histogram show better performances than other approaches, but they have computation load problem. In this paper, we proposed a scene change detection algorithm with fast and accurate performance using the vertical and horizontal blocked slice images and their macro block informations. We apply graph cut partitioning algorithm for clustering and partitioning of video sequence using generated spatio-temporal histogram. When making spatio-temporal histogram, we only use the central block on vertical and horizontal direction for performance improvement. To detect camera and object movement as well as various special effects accurately, we utilize the motion vector and type information of the macro block.

• Journal of the Korea Computer Graphics Society
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• v.23 no.3
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• pp.9-17
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• 2017

This study proposes a third-person virtual reality content production pipeline to provide users with a new experience and presence in a new virtual reality environment. For this purpose, we first create third-person virtual reality content, which includes a story, fun factors, and game characteristic. It consists of a tutorial scene in which a user can pre-learn the proposed interface suitable for a third person different from existing virtual reality content and a content scene that achieves its purpose by using game factors based on the background story. Next, we design an interface suitable for the third-person virtual reality content. This study proposes an interface in which users can interact with a virtual environment or object by using their hand. The proposed interface consists of three steps: character movement, virtual object selection with multiple selection, and 3D menu control using virtual space. Finally, through the survey experiment, third-person virtual reality content produced based on the proposed interface was confirmed to be easily controlled while ensuring high satisfaction.

• Cartoon and Animation Studies
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• s.50
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• pp.43-73
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• 2018

This is a study on 'Objet' in animation culture art education. Research on the use of Objet in modern art is actively under way. From Cubism to Dadaism, Surrealism, Futurism and Pop art, it is no exaggeration to say that the Objet is stepping with modern art. In addition, Objet has a remarkable value in the field of visual arts expressing 'motion' such as kinetic art, video art, media art, and animation. However, there are not many cases of classifying and studying the types of Objets used in artworks. Therefore, this researcher has been influenced by the surrealism discourse and prepared six types of Objets type analysis framework. And the research focused on 'the aesthetic emotion and educational aspect of creativity improvement' of Objet animation was conducted. The type analysis framework is named as a drawing Objet, Objet of existence, a morphine Objet, epidermis Objet, assigned Objet and assemblage Objet and this type is presented and analyzed with case image. The data used in this study was focused on the outcome of Objet animation that were trained for non-experts in culture and arts education. This aesthetic emotion refers to Freud's desire for life (Eros) as Attraction, and desire for death (Thanatos) as Uncanny (fearful unfamiliarity) and explains the conflicting concept with the Animism, the indigenous religion. Next, educational aspects of Objet animation creativity improvement in relation to the term 'functional fixedness' was discussed as described by Gestalt psychologist Karl Duncker (1903-1940). Overcoming the functional fixedness is a phenomenon that is fixed only to the functional aspects of things and can't be changed. In this study, the educational aspect of creativity improvement was demonstrated as a case of overcoming the functional fixedness through 'Objet Animation' culture and art education. Ultimately, this study is to prove the aesthetic emotion and creativity of the Objet animation by analyzing Objet types. Furthermore, it is meaningful to suggest direction when using 'Objet Animation' in culture and arts education.

• Journal of Korea Society of Industrial Information Systems
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• v.12 no.5
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• pp.39-46
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• 2007

Research on human identification in ubiquitous environment has recently attracted a lot of attention. As one of those research, gait recognition is an efficient method of human identification using physical features of a walking person at a distance. In this paper, we present a human shape extraction and tracking for gait recognition using geodesic active contour models(GACMs) combined with mean shift algorithm The active contour models (ACMs) are very effective to deal with the non-rigid object because of its elastic property. However, they have the limitation that their performance is mainly dependent on the initial curve. To overcome this problem, we combine the mean shift algorithm with the traditional GACMs. The main idea is very simple. Before evolving using level set method, the initial curve in each frame is re-localized near the human region and is resized enough to include the targe region. This mechanism allows for reducing the number of iterations and for handling the large object motion. The proposed system is composed of human region detection and human shape tracking modules. In the human region detection module, the silhouette of a walking person is extracted by background subtraction and morphologic operation. Then human shape are correctly obtained by the GACMs with mean shift algorithm. In experimental results, the proposed method show that it is extracted and tracked efficiently accurate shape for gait recognition.

• Journal of Internet Computing and Services
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• v.25 no.1
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• pp.29-37
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• 2024

In this paper, we propose an efficient image processing system to detect and track the movement of specific objects such as patients. The proposed system extracts the outline area of an object from a binarized difference image by applying a thinning algorithm that enables more precise detection compared to previous algorithms and is advantageous for mixed-mode design. The binarization and thinning steps, which require a lot of computation, are designed based on RTL (Register Transfer Level) and replaced with optimized hardware blocks through logic circuit synthesis. The designed binarization and thinning block was synthesized into a logic circuit using the standard 180n CMOS library and its operation was verified through simulation. To compare software-based performance, performance analysis of binary and thinning operations was also performed by applying sample images with 640 × 360 resolution in a 32-bit FPGA embedded system environment. As a result of verification, it was confirmed that the mixed-mode design can improve the processing speed by 93.8% in the binary and thinning stages compared to the previous software-only processing speed. The proposed mixed-mode system for object recognition is expected to be able to efficiently monitor patient movements even in an edge computing environment where artificial intelligence networks are not applied.

• The KIPS Transactions:PartB
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• v.10B no.1
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• pp.95-102
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• 2003

In surveillance video system, there are many classes of images and some spatial regions are more important than other regions. The conventional compression method in this system have been compressed there full frames without classfying them depend on their important parts. To improve the accuracy of the image coding and deliver effective compression for the surveillance video system, it was necessary to separate the regions according to their importance. In this paper, we propose a new effective surveillance video image compression method. The proposed scheme defines importance based three-level region of interest block in a frame, such as background, motion object block, and the feature object block. A captured video image frame can be separated to these three different levels of block regions. And depends on the priority, each block can be modified and compressed in different resolution, compression ratio and qualify factor. Therefore, in surveillance video system, this algorithm not only reduces the image processing time and space, but also guarantees the Important image data in high quality to acquire the system's goal.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.8 no.3
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• pp.945-953
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• 2018

In this paper, we use 3-D LIDAR for obstacle detection and avoidance maneuver for autonomous unmanned operation. It is aimed to avoid obstacle avoidance in unmanned water under marine condition using only single sensor. 3D lidar uses Quanergy's M8 sensor to collect surrounding obstacle data and includes layer information and intensity information in obstacle information. The collected data is converted into a three-dimensional Cartesian coordinate system, which is then mapped to a two-dimensional coordinate system. The data including the obstacle information converted into the two-dimensional coordinate system includes noise data on the water surface. So, basically, the noise data generated regularly is defined by defining a hypothetical region of interest based on the assumption of unmanned water. The noise data generated thereafter are set to a threshold value in the histogram data calculated by the Vector Field Histogram, And the noise data is removed in proportion to the amount of noise. Using the removed data, the relative object was searched according to the unmanned averaging motion, and the density map of the data was made while keeping one cell on the virtual grid map. A polar histogram was generated for the generated obstacle map, and the avoidance direction was selected using the boundary value.

• Cartoon and Animation Studies
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• s.49
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• pp.87-112
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• 2017

Overlap what images are laid on top of each other performs various purposes of artistic expressions. Especially, overlap to describe motion has been placed on lots of art fields analysing and connecting each part of motion. This kind of overlap is called as 'Locomotive overlap' and it is defined as 'Technique for multiplication to arrange simultaneously motions of single object on one screen'. Locomotive overlap was started from fine art and photography, so this static kind of it is classified as 'Static locomotive overlap'. Afterwards, film and animation succeeded static locomotion overlap and realized real dynamic locomotive overlap with moving images, so this dynamic kind of it is classified as 'Dynamic locomotive overlap'. Most of all, by Norman McLaren accomplished its own artistic value and aesthetics in locomotive overlap has been placed in the center of the history of locomotive overlap, so to analyze this work and to research before and after it will confirm context and artistic achievements of locomotive overlap. Nowdays locomotive overlap is extending its technology and dimension more and more on the strength of development of digital technology. Some of works using digital technology show new possibilities of locomotive overlap by reinterpreting original media and concept of . Ultimately, this research for locomotive overlap focusing on the analysis of confirms artistic achievements of locomotive overlap and suggests to contemplate the meaning and new possibilities of it.

• Korean Journal of Applied Biomechanics
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• v.25 no.2
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• pp.157-165
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• 2015

Object : The goals of this research were to make Performance Enhanced Model(PE) taken the largest performance index (PI) through artificial variation of principle components calculated by principle component analysis for trial data, and to verify the effect through comparing kinematic factors between trial data (Raw) and PE. Method : Ten subjects (5 men, 5 women) were recruited and 80% of their maximal record was considered. The PI is a regression equation. In order to develop PE, we extracted Principle components from trial position data (by Principle Components Analysis (PCA)). Before PCA, we made 17 position data to 3 row matrix according to components. We calculated 3 eigen value (principle components) through PCA. And except Y (medial-lateral direction) component (because motion of Y component is small), principle components of X (anterior-posterior direction) and Z (vertical direction) components were changed as following. Changed principle components = principle components + principle components ${\times}$ k. After changing the each principle component, we reconstructed position data using the changed principle components and calculated performance index (PI). A Paired t-test was used to compare Raw data and Performance Enhanced Model data. The level of statistical significance was set at $p{\leq}0.05$. Result : The PI was significantly increased about 12.9kg at PE ($101.92{\pm}6.25$) when compared to the Raw data ($91.29{\pm}7.10$). It means that performance can be increased by optimizing 3D positions. The difference of kinematic factors as follows : the movement distance of the bar from start to lock out was significantly larger (about 1cm) for PE, the width of anterior-posterior bar position in full phase was significantly wider (about 1.3cm) for PE and the horizontal displacement toward the weightlifter after beginning of descent from maximal height was significantly greater (about 0.4cm) for PE. Additionally, the minimum knee angle in the 2-pull phase was significantly smaller (approximately 2.7cm) for the PE compared to that of the Raw. PE was decided at proximal position from the Raw (origin point (0,0)) of PC variation). Conclusion : PI was decided at proximal position from the Raw (origin point (0,0)) of PC variation). This means that Performance Enhanced Model was decided by similar motion to the Raw without a great change. Therefore, weightlifters could be accept Performance Enhanced Model easily, comfortably and without large stress. The Performance Enhance Model can provide training direction for athletes to improve their weightlifting records.