Hyung-Je Cho

Efficient modeling of numerous trees by introducing growth volume for real-time virtual ecosystems

This study suggests a growth volume system for the efficient modeling of numerous trees for a real‐time virtual ecosystem. To increase the efficiency of the real‐time system and to allow natural tree generation, the basic tree modeling system obtains its growth rule by means of botany‐based self‐organizing under a recursive hierarchy structure. On the basis of this rule, growth volume was introduced and controlled to generate numerous trees in a virtual ecosystem more intuitively, which allows the generation of various trees. The reality of the expression was increased by including the effects of external factors, such as light, physical obstacles, and other trees. Finally, an instancing‐based branch control procedure was added to enable an efficient rendering of the real‐time ecosystem. Experiments were performed to verify whether various and natural trees could be generated and numerous trees in the virtual ecosystem can be easily modeled on the basis of the suggested growth volume, which shows the efficiency of the real‐time ecosystem. Copyright

Procedural modeling of trees based on convolution sums of divisor functions for real‐time virtual ecosystems

This study proposes a novel procedural modeling method using convolution sums of divisor functions to model a variety of natural trees in a virtual ecosystem efficiently. The basic structure of the modeling method defines the growth grammar, including the branch propagation, a growth pattern of branches and leaves, and a process of growth deformation for various tree generation. Here, the proposed procedural method for trees is to utilize convolution sums of divisor functions as a novel approach. The structure of convolution sums has branch propagation of a uniform pattern, which is controllable, so that it is efficient for real‐time virtual ecosystem construction. Furthermore, it can process changes of environment factors or growth deformation for various and unique tree generation simply through the properties of divisor functions. Finally, an experiment is performed in order to evaluate our proposed modeling method whether it can generate natural and various tree models, and a real‐time virtual ecosystem of a large area where a variety of trees are presented using the modeling method can be constructed efficiently.Copyright

Human Action Recognition by Inference of Stochastic Regular Grammars

In this paper, we present a new method of recognizing human actions by inference of stochastic grammars for the purpose of automatic analysis of nonverbal actions of human beings. We applied the principle that a human action can be defined as a combination of multiple articulation movements. We measure and quantize each articulation movements in 3D and represent two sets of 4-connected chain code for xy and zy projection planes, so that they are appropriate for the stochastic grammar inference method. This recognition method is tested by using 900 actions of human upper body. The result shows a comparatively successful achievement of 93.8% recognition rate through the experiments of 8 action types of head and 84.9% recognition rate of 60 action types of upper body.

Inferring stochastic regular grammar with nearness information for human action recognition

In this paper, we present an extended scheme of human action recognition with nearness information between hands and other body parts for the purpose of automatically analyzing nonverbal actions of human beings. First, based on the principle that a human action can be defined as a combination of multiple articulation movements, we apply the inference of stochastic grammars. We measure and quantize each human action in 3D coordinates and make two sets of 4-chain-code for xy and zy projection planes, so that they are appropriate for the stochastic grammar inference method. Next, we extend the stochastic grammar inferring method by applying nearness information. We confirm that various physical actions are correctly classified against a set of real-world 3D temporal data with this method in experiments. Our experiments show that this extended method reveals comparatively successful achievement with a 92.7% recognition rate of 60 movements of the upper body.

Tree Growth Model Design for Realistic Game Landscape Production

In this study, a tree growth model is designed to represent a variety of trees consisting of a outdoor terrain of game efficiently and naturally. The proposed tree growth model is an integrated tree growth model, and is configured using the following approaches: (1) the tree modeling method based on growth volume and the convolution sums of divisor functions, which is used to model a variety kind of trees more intuitively and naturally; (2) a rendering method using a level of detail of branch based on instancing for real-time processing of numerous trees with complicated structures; and (3) a combination of the above methods to efficiently implement a game landscape. The natural and diverse growths of trees that emerged using the proposed tree growth model is evaluated through experimentation, along with the possibility of implementing the natural game landscape and the efficiency of real-time processing.

Warping of 2D Facial Images Using Image Interpolation by Triangle Subdivision

ABSTRACT Image warping is a technology to transform input images to be suitable for given conditions and has been recently utilized in changing face shape of characters in the field of movies or animation. Mesh warping which is one of warping methods that change shapes based on the features of face forms warping images by forming rectangular mesh groups around the eyes, nose, and mouth and matching them 1:1. This method has a problem in the resultant images are distorted in the segments of boundaries between meshes when there are errors in mesh control points or when meshes have been formed as many small area meshes. This study proposes a triangle based image interpolation technique to minimize the occurrence of errors in the process of forming natural warping images of face and process accurate results with a small amount of arithmetic operation and a short time. First, feature points that represent the face are found and these points are connected to form basic triangle meshes. The fact that the proposed method can reduce errors occurring in the process of warping while reducing the amount of arithmetic operation and time is shown through experiments. Keywords : Facial image warping(얼굴 영상 워핑), Feature-based method(특징기반 방법), Triangle subdivision(삼각형 반복분할), Image interpolation(영상보간법), Mesh warping(메쉬워핑)

Erkennung von Körperbewegungsmustern durch Automaten

In den letzten Jahren ist das Interesse an der automatischen Erkennung von Korperbewegungen auf der Basis optischer Information ganz erheblich gestiegen. Die Vielfalt der Einsatzmoglichkeiten beweist, das es sich nicht nur um das Interesse einer kleinen Schar von Experten handelt, z.B.: Ganganalyse, automatische Kommentierung von Sequenzen in Video-Datenbanken, die die Bewegungen von Menschen beinhalten [Cle95], drahtlose Mensch-Maschine-Schnittstellen fur Virtual- Reality-Anwendungen [Bec97], Uberwachungs-systeme, Interpretation von Zeichensprachen [Bra96][Sut96] und Choreographie von Tanz und Ballett [Cam95]. Fur die automatische Erkennung der Korperbewegungen in Videobildern mussen mehrere Phasen durchgefuhrt werden: Initiale Detektion einer Person, Verfolgen der Person, Segmentierung des Korpers, Extrahierung der einzelnen Korperteile und Erkennung der Korperbewegungsmuster. Es sind schon mehrere Systeme in speziellen Gebieten entwickelt worden, die die Korperbewegungen erkennen konnen, z.B. Sensei [Bec97], ARGo [Bra96], First Sight [Leu95] usw. Zur Klassifikationsmethode von Bewegungsmustern wurden Phase Space Methode [Cam95], HMM (Hidden Markov Model) [Bec97][Bra96], Dynamic Time Warping [Gav95], Template Matching [Sut96] usw. angewendet. Der Schwerpunkt dieses Beitrags liegt auf der Klassifikationsmethode von Korperbewegungsmustern mit dem Ziel, die nonverbalen Korpersignale zu erkennen. Eine Korperbewegung enthalt gleichzeitig mehrere Korperteilbewegungen mit verschiedenen Bewegungsvektoren.