Theses supervised by Doç. Dr. Uğur Güdükbay
10 theses · İhsan Doğramacı Bilkent University
Yerleşim alanlarının görüntülenmesi
Modeling and visualization of large geometric environments is a popular researcharea in computer graphics. In this dissertation, a framework for modeling andstereoscopic visualization of large and complex urban environments is presented.The occlusion culling and view-frustum culling is performed to eliminate mostof the geometry that do not contribute to the user?s ï¬nal view. For the occlu-sion culling process, the shrinking method is employed but performed using anovel Minkowski-diï¬erence-based approach. In order to represent partial visibil-ity, a novel building representation method, called the slice-wise representationis developed. This method is able to represent the preprocessed partial visibilitywith huge reductions in the storage requirement. The resultant visibility list isrendered using a graphics-processing-unit-based algorithm, which perfectly ï¬tsinto the proposed slice-wise representation. The stereoscopic visualization de-pends on the calculated eye positions during walkthrough and the visibility listsfor both eyes are determined using the preprocessed occlusion information. Theview-frustum culling operation is performed once instead of two for both eyes.The proposed algorithms were implemented on personal computers. Performanceexperiments show that, the proposed occlusion culling method and the usage ofthe slice-wise representation increase the frame rate performance by 81 %; thegraphics-processing-unit-based display algorithm increases it by an additional315 % and decrease the storage requirement by 97 % as compared to occlusionculling using building-level granularity and not using the graphics hardware. Weshow that, a smooth and real-time visualization of large and complex urban en-vironments can be achieved by using the proposed framework.Keywords: Stereoscopic visualization, slice-wise representation, space subdivi-sion, octree, occlusion culling, occluder shrinking, Minkowski diï¬erence, from-region visibility, urban visualization, visibility processing.iv
Üç boyutlu bulanık dokular kullanan karma saç modeli
Human hair modeling and rendering have always been a challenging topic incomputer graphics. The techniques for human hair modeling consist of explicitgeometric models as well as volume density models. Recently, hybrid clustermodels have also been successful in this subject. In this study, we present anovel three dimensional texture model called 3D Fuzzy Textures and algorithmsto generate them. Then, we use the developed model along with a cluster modelto give human hair complex hairstyles such as curly and wavy styles. Our modelrequires little user eï¬ort to model curly and wavy hair styles. With this study,we aim at eliminating the drawbacks of the volume density model and the clusterhair model with 3D fuzzy textures. A three dimensional cylindrical texture map-ping function is introduced for mapping purposes. Current generation graphicshardware is utilized in the design of rendering system enabling high performancerendering.Keywords: Hair modeling, hair rendering, curly hair, wavy hair, cluster hairmodel, volume density model, 3D texture, 3D texture mapping.iii
Gerçek zamanlı parametrik gezme hareketi türetilmesi
Reuse and blending of captured motions for creating realistic motions of human body is considered as one of the challenging problems in animation and computer graphics. Locomotion (walking, running and jogging) is one of the most common types of daily human motion. Based on blending of multiple motions, we propose a two-stage approach for generating locomotion according to user-specified parameters, such as linear and angular velocities. Starting from a large dataset of various motions, we construct a motion graph of similar short motion segments. This process includes the selection of motions according to a set of predefined criteria, the correction of errors on foot positioning, pre-adjustments, motion synchronization, and transition partitioning. In the second stage, we generate an animation according to the specified parameters by following a path on the graph during run-time, which can be performed in real-time. Two different blending techniques are used at this step depending on the number of the input motions: blending based on scattered data interpolation and blending based on linear interpolation. Our approach provides an expandable and efficient motion generation system, which can be used for real time applications.
Sanal şehir modelleme ve nüfuslandırma: Otomatik bina modeli üretimi ve acil durumlar icin kalabalık simülasyonu
In this thesis, we present an automatic building generation method based on procedural modeling approach, and a crowd animation system that simulates a crowd of pedestrians inside a city. While modeling the buildings, to achieve complex and consistent geometries we use shape grammars. The derivation process incorporates randomness so the produced models have the desired variation. The end shapes of the building models could be defined in a certain extent by the derivation rules. The behavior of human crowds inside a city is affected by the simulation scenario. In this thesis, we specifically intend to simulate the virtual crowds in emergency situations caused by an incident, such as a fire, an explosion, or a terrorist attack. We prefer to use a continuum dynamics-based approach to simulate the escaping crowd, which produces more efficient simulations than the agent-based approaches. Only the close proximity of the incident region, which includes the crowd affected by the incident, is simulated. In order to speed up the animation and visualization of the resulting simulation, we employ an offline occlusion culling technique. During runtime, we animate and render a pedestrian model only if it is visible to the user. In the pre-processing stage, the navigable area of the scene is decomposed into a grid of cells and the from-region visibility of these cells is computed with the help of hardware occlusion queries.
Gözetim videoları için senaryo tabanlı sorgulama çatısı
Video surveillance has become one of the most interesting and challenging application areas in video processing domain. Automated access to the semantic content of surveillance videos to detect anomalies is among the basic tasks; however due to the high variability of the visual features and large size of the video input, it still remains a challenging issue. A considerable amount of research dealing with automated access to video surveillance has appeared in the literature; however, significant semantic gaps in event models and content-based access still remain. In this thesis, we propose a scenario-based query processing framework for video surveillance archives, especially for indoor environments. A scenario is specified as a sequence of event predicates that can be enriched with object-based low-level features and directional predicates. We also propose a keyframe labeling technique, which assigns labels to keyframes extracted based on keyframe detection algorithm, hence transforms the input video to an event sequence based representation. The keyframe detection scheme relies on an inverted tracking scheme, which is a view-based representation of the actual content by an inverted index. We also devise mechanisms based on finite state automata using this event sequence representation to detect a typical set of anomalous events in the scene, which are also used for meta-data extraction. Our query processing framework also supports inverse querying and view-based querying, for after-the-fact activity analysis, since the inverted tracking scheme effectively tracks the moving objects and enables view-based addressing of the scene. We propose a specific surveillance query language to express the supported query types in a scenario-based manner. We also present a visual query specification interface devised to enhance the query-specification process. It has been shown through performance experiments that the keyframe labeling algorithm significantly reduces the storage requirements and yields a reasonable anomaly detection performance. We have also conducted performance experiments to show that our query processing technique has a high expressive power and satisfactory retrieval accuracy in video surveillance.
Kitlelerden güruhlara: Psikolojik faktörlerle kalabalık simülasyonu
Crowd simulation has a wide range of application areas such as biological and social modeling, military simulations, computer games and movies. Simulating the behavior of animated virtual crowds has been a challenging task for the computer graphics community. As well as the physical and the geometrical aspects,the semantics underlying the motion of real crowds inspire the design and implementation of virtual crowds. Psychology helps us understand the motivations of the individuals constituting a crowd. There has been extensive research on incorporating psychological models into the simulation of autonomous agents.However, in our study, instead of the psychological state of an individual agent as such, we are interested in the overall behavior of the crowd that consists of virtual humans with various psychological states. For this purpose, we incorporate the three basic constituents of affect: personality, emotion and mood. Each of these elements contribute variably to the emergence of different aspects of behavior. We thus examine, by changing the parameters, how groups of people with different characteristics interact with each other, and accordingly, how the global crowd behavior is influenced.In the social psychology literature, crowds are classified as mobs and audiences. Audiences are passive crowds whereas mobs are active crowds with emotional, irrational and seemingly homogeneous behavior. In this thesis, we examine how audiences turn into mobs and simulate the common properties of mobs to create collective misbehavior. So far, crowd simulation research has focused on panicking crowds among all types of mobs. We extend the state of the art to simulate different types of mobs based on the taxonomy. We demonstrate various scenarios that realize the behavior of distinct mob types.Our model is built on top of an existing crowd simulation system, HiDAC (High-Density Autonomous Crowds). HiDAC provides us with the physical and low-level psychological features of crowds. The user normally sets these parameters to model the non-uniformity and diversity of the crowd. In our work, we free the user of the tedious task of low-level parameter tuning, and combine all these behaviors in distinct psychological factors. We present the results of our experiments on whether the incorporation of a personality model into HiDAC was perceived as intended.
Uyarlanabilir ızgaralardan yararlanarak sanal kentsel ortamlarda gerçek zamanlı kalabalık simulasyonu
Crowd simulation is a relatively new research area, attracting increasing attentionfrom both academia and industry. This thesis proposes Adaptive Grids, anovel hybrid approach for controlling the behavior of agents in a virtual crowd. Inthis approach, the motion of each agent within the crowd is planned consideringboth global and local path planning strategies. For global path planning, a cellularadaptive grid is constructed from a regular navigation map that representsthe 2-D topology of the simulation terrain. A navigation graph with efficientsize is then pre-computed from the adaptive grid for each possible agent goal.Finally, the navigation graph is used to generate a potential field on the adaptivegrid by using the connectivity information of the irregular cells. Global pathplanning per agent has constant time complexity. For local path planning, HelbingTraffic-Flow model is used to avoid obstacles and agents. Potential forcesare then applied on each agent considering the local and global decisions of theagent, while providing each agent the freedom to act independently.
Karmaşık 3B arazilerin gerçek-zamanlı olarak simgelenmesi, düzenlenmesi ve görselleştirilmesi
Terrain rendering is a crucial part of many real-time computer graphics applications such as video games and visual simulations. It provides the main frame-of-reference for the observer and constitutes the basis of an imaginary or simulated world that encases the observer. Storing and rendering terrain models in real-time applications usually require a specialized approach due to the sheer magnitude of data available and the level of detail demanded. The easiest way to process and visualize such large amounts of data in real-time is to constrain the terrain model in several ways. This process of regularization decreases the amount of data to be processed and also the amount of processing power needed at the cost of expressivity and the ability to create interesting terrains.The most popular terrain representation, by far, used by modern real-time graphics applications is a regular 2D grid where the vertices are displaced in a third dimension by a displacement map, conventionally called a height map. It is the simplest and fastest possible terrain representation, but it is not possible to represent complex terrain models that include interesting terrain features such as caves, overhangs, cliffs and arches using a simple 2D grid and a height map. We propose a novel terrain representation combining the voxel and height map approaches that is expressive enough to allow creating complex terrains with caves, overhangs, cliffs and arches, and efficient enough to allow terrain editing, deformations and rendering in real-time. We also explore how to apply lighting, texturing, shadowing and level-of-detail to the proposed terrain representation.
Uçuş zamanı kameraları kullanan gerçek zamanlı fizik tabanlı arttırılmış giyinme kabini
This thesis proposes a framework for a real-time physically-based augmented cloth fitting environment. The required 3D meshes for the human avatar and apparels are modeled with specific constraints. The models are then animated in real-time using input from a user tracked by a depth sensor. A set of motion filters are introduced in order to improve the quality of the simulation. The physical effects such as inertia, external and forces and collision are imposed on the apparel meshes. The avatar and the apparels can be customized according to the user. The system runs in real-time on a high-end consumer PC with realistic rendering results.
El hareketlerine dayalı gelişmiş arayüz ile sanal modelleme
In this study, we propose a virtual reality application that can be utilized to design preliminary/conceptual models similar to real world clay sculpting. The proposed system makes use of the innovative gestural interface that enhances the experience of the human-computer interaction. The gestural interface employs advanced motion capture hardware namely data gloves and six-degrees-of-freedom position tracker instead of classical input devices like keyboard or mouse. The design process takes places in the virtual environment that contains volumetric deformable model, design tools and a virtual hand that is driven by the data glove and the tracker. The users manipulate the design tools and the deformable model via the virtual hand. The deformation on the model is done by stuffing or carving material (voxels) in or out of the model with the help of the tools or directly by the virtual hand. The virtual sculpting system also includes volumetric force feedback indicator that provides visual aid. We also offer a mouse like interaction approach in which the users can still interact with conventional graphical user interface items such as buttons with the data glove and tracker. The users can also control the application with gestural commands thanks to our real time trajectory based dynamic gesture recognition algorithm. The gesture recognition technique exploits a fast learning mechanism that does not require extensive training data to teach gestures to the system. For recognition, gestures are represented as an ordered sequence of directional movements in 2D. In the learning phase, sample gesture data is filtered and processed to create gesture recognizers, which are basically finite-state machine sequence recognizers. We achieve real time gesture recognition by these recognizers without needing to specify gesture start and end points. The results of the conducted user study show that the proposed method is very promising in terms of gesture detection and recognition performance (73\% accuracy) in a stream of motion. Additionally, the assessment of the user attitude survey denotes that the gestural interface is very useful and satisfactory. One of the novel parts of the proposed approach is that it gives users the freedom to create gesture commands according to their preferences for selected tasks. Thus, the presented gesture recognition approach makes the HCI process more intuitive and user specific.