Browsing by Author "Demirci, Serkan"

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Ankara Atatürk Lisesi Eğitim Vakfı
(Bilkent University, 2014) Demirci, Serkan; Banak, Ali Erdem; Çiçek, Caner; Çamkıran, Özge; Emre Köksal, Vahit
Open Access
Antibacterial activity of cyclodextrin-Azo dye inclusion complex encapsulated electrospun polycaprolactone nanofibers
(Wiley-VCH Verlag GmbH & Co. KGaA, 2021-10-12) Demirci, Serkan; Çelebioğlu, Aslı; Demirci, S. K.; İdil, Ö.
Polycaprolactone (PCL) nanofibers incorporating azo dye/γ-cyclodextrin inclusion complex (Azo/γ-CD-IC) were successfully produced. The characteristics of the Azo/γ-CD-IC and PCL/Azo/γ-CD-IC nanofibers were investigated by X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR) and thermogravimetric analysis (TGA). Based on the SEM analysis the prepared nanofiber has a smooth surface with a size diameter below 500 nm. Meanwhile, the thermal stability of Azo was further improved after being embedded into Azo/γ-CD-IC and the PCL/Azo/γ-CD-IC nanofibers. Proton nuclear magnetic resonance (1H-NMR) was used to calculate the molar ratio of Azo/γ-CD. The antibacterial activity of the PCL/Azo/γ-CD-IC and PCL/Azo nanofibers was investigated using colony counting method and bacterial strains of Escherichia coli and Staphylococcus aureus were used. The results indicated that PCL/Azo/γ-CD-IC nanofibers have enhanced antibacterial activity against Escherichia coli and Staphylococcus aureus compared to PCL/Azo owing to inclusion complexation. Therefore, these PCL/Azo/γ-CD-IC nanofibers might have potential applications in the biomedical field.
Open Access
Augmentation of virtual agents in real crowd videos
(Springer, 2019) Doğan, Yalım; Demirci, Serkan; Güdükbay, Uğur; Dibeklioğlu, Hamdi
Augmenting virtual agents in real crowd videos is an important task for different applications from simulations of social environments to modeling abnormalities in crowd behavior. We propose a framework for this task, namely for augmenting virtual agents in real crowd videos. We utilize pedestrian detection and tracking algorithms to automatically locate the pedestrians in video frames and project them into our simulated environment, where the navigable area of the simulated environment is available as a navigation mesh. We represent the real pedestrians in the video as simple three-dimensional (3D) models in our simulation environment. 3D models representing real agents and the augmented virtual agents are simulated using local path planning coupled with a collision avoidance algorithm. The virtual agents augmented into the real video move plausibly without colliding with static and dynamic obstacles, including other virtual agents and the real pedestrians.
Open Access
Bounding volume hierarchy-tetrahedralization hybrid acceleration structure for ray tracing
(2020-12) Demirci, Serkan
The computational cost of the ray-tracing method is directly proportional to the number of ray-surface intersection tests. The naive ray-tracing algorithm requires O(N) computational cost for the ray-surface intersection calculations where N is the number of primitives in the scene. Ray tracing acceleration data structures like the regular grid, bounding volume hierarchy (BVH), kd-tree, constrained tetrahedralization, has been developed to reduce the number of rayobject intersection tests to speed-up ray tracing. We propose a hybrid acceleration structure, the Bounding Volume HierarchyTetrahedral mesh hybrid (BTH) acceleration structure, that can be used to speedup ray tracing. BTH structure is composed of a BVH hierarchy where some of the leaves of the BVH hierarchy contain tetrahedralizations. We propose an algorithm for the construction of the BTH structure. We describe methods for approximating the average nearest-hit cost of a tetrahedralization, which we use for the construction of BTH. Besides, we can adapt the proposed BTH structure for dynamic scenes with hierarchical motion. We describe a two-level BVH-BTH acceleration structure for rendering animated scenes. We test the proposed BTH structure using various scenes. For some of the experiments, the BTH structure performs better against other acceleration structures in terms of rendering times. We perform experiments for animated scenes. We show that the two-level BTH structure outperforms the two-level BVH structure for the tested dynamic scenes.
Open Access
Compact tetrahedralization-based acceleration structures for ray tracing
(Springer, 2022-10) Aman, Aytek; Demirci, Serkan; Güdükbay, Uğur
We propose compact and efficient tetrahedral mesh representations to improve the ray-tracing performance. We reorder tetrahedral mesh data using a space-filling curve to improve cache locality. Most importantly, we propose efficient ray-traversal algorithms. We provide details of the regular ray-tracing operations on tetrahedral meshes and the GPU implementation of our traversal method. We demonstrate our findings through a set of comprehensive experiments. Our method outperforms existing tetrahedral mesh-based traversal methods and yields comparable results to the traversal methods based on the state-of-the-art acceleration structures such as k-dimensional (k-d) tree and Bounding Volume Hierarchy (BVH) in terms of speed. Storage-wise, our method uses less memory than its tetrahedral mesh-based counterparts, thus allowing larger scenes to be rendered on the GPU. Graphic Abstract: [Figure not available: see fulltext.] © 2022, The Visualization Society of Japan.
Open Access
Human movement personality detection parameters
(IEEE, 2024-06-23) Sonlu, Sinan; Dogan, Yalım; Ergüzen, Arçin Ülkü; Ünalan, Musa Ege; Demirci, Serkan; Durupinar, Funda; Güdükbay, Uğur
In this study, we develop a system that detects apparent personality traits from animation data containing human movements. Since the datasets that can be used for this purpose lack sufficient variance, we determined labels for the samples in two datasets containing human animations, in terms of the Five Factor Personality Theory, with the help of a user study. Using these labels, we identified movement parameters highly dependent on personality traits and based on Laban Movement Analysis categories. The artificial neural networks we trained for personality analysis from animation data show that models that take the motion parameters determined in the study as input have a higher accuracy rate than models that take raw animation data as input. Therefore, using the parameters determined in this study to evaluate human movements in terms of their personality traits will increase the systems' success.
Open Access
Hybrid image-/data-parallel rendering using island parallelism
(Institute of Electrical and Electronics Engineers, 2022-12-06) Zellmann, S.; Wald, I.; Barbosa, J.; Demirci, Serkan; Şahıstan, Alper; Güdükbay, Uğur
In parallel ray tracing, techniques fall into one of two camps: image-parallel techniques aim at increasing frame rate by replicating scene data across nodes and splitting the rendering work across different ranks, and data-parallel techniques aim at increasing the size of the model that can be rendered by splitting the model across multiple ranks, but typically cannot scale much in frame rate. We propose and evaluate a hybrid approach that combines the advantages of both by splitting a set of N x M ranks into M islands of N ranks each and using data-parallel rendering within each island and image parallelism across islands. We discuss the integration of this concept into four wildly different parallel renderers and evaluate the efficacy of this approach based on multiple different data sets.
Open Access
Multi-level tetrahedralization-based accelerator for ray-tracing animated scenes
(John Wiley & Sons Ltd., 2021-06-01) Aman, Aytek; Demirci, Serkan; Güdükbay, Uğur; Wald, I.
We describe a hybrid acceleration structure for ray tracing. The hybrid structure is a Bounding Volume Hierarchy (BVH) where the leaf nodes are tetrahedralized for a decent ray-surface intersection performance. We use the hybrid acceleration structure (BTH) in a two-level acceleration structure for rendering animated scenes. There is a BVH at the top level in this two-level structure and the proposed hybrid structure (BTH) at the bottom level. We test the proposed two-level structure (BVH-BTH) for various animated scenes and obtained promising results against other acceleration structures in terms of rendering times. The two-level BVH-BTH structure outperforms the two-level BVH structure for the tested dynamic scenes.
Open Access
State-of-the-art in large-scale volume visualization beyond structured data
(Eurographics and John Wiley & Sons Ltd., 2023-06-27) Sarton, J.; Zellmann, S.; Demirci, Serkan; Güdükbay, Uğur; Alexandre-Barff, W.; Lucas, L.; Dischler, J. M.; Wesner, S.; Wald, I.; Alliez, Pierre; Wimmer, Michael
Volume data these days is usually massive in terms of its topology, multiple fields, or temporal component. With the gap between compute and memory performance widening, the memory subsystem becomes the primary bottleneck for scientific volume visualization. Simple, structured, regular representations are often infeasible because the buses and interconnects involved need to accommodate the data required for interactive rendering. In this state-of-the-art report, we review works focusing on large-scale volume rendering beyond those typical structured and regular grid representations. We focus primarily on hierarchical and adaptive mesh refinement representations, unstructured meshes, and compressed representations that gained recent popularity. We review works that approach this kind of data using strategies such as out-of-core rendering, massive parallelism, and other strategies to cope with the sheer size of the ever-increasing volume of data produced by today's supercomputers and acquisition devices. We emphasize the data management side of large-scale volume rendering systems and also include a review of tools that support the various volume data types discussed.
Open Access
Towards understanding personality expression via body motion
(2024-05-29) Sonlu, Sinan; Dogan, Yalim; Ergüzen, Arçin Ülkü; Ünalan, Musa Ege; Demirci, Serkan; Durupınar, Funda; Güdükbay, Uğur
This work addresses the challenge of data scarcity in personality-labeled datasets by introducing personality labels to clips from two open datasets, ZeroEGGS and Bandai, which provide diverse full-body animations. To this end, we present a user study to annotate short clips from both sets with labels based on the Five-Factor Model (FFM) of personality. We chose features informed by Laban Movement Analysis (LMA) to represent each animation. These features then guided us to select the samples of distinct motion styles to be included in the user study, obtaining high personality variance and keeping the study duration and cost viable. Using the labeled data, we then ran a correlation analysis to find features that indicate high correlation with each personality dimension. Our regression analysis results indicate that highly correlated features are promising in accurate personality estimation. We share our early findings, code, and data publicly.
Open Access
Visual analysis of large multi-dield AMR data on GPUs using interactive volume lines
(IEEE, 2023-12-20) Zellmann, S.; Demirci, Serkan; Güdükbay, Uğur
To visually compare ensembles of volumes, dynamic volume lines (DVLs) represent each ensemble member as a 1D polyline. To compute these, the volume cells are sorted on a space-filling curve and scaled by the ensemble’s local variation. The resulting 1D plot can augment or serve as an alternative to a 3D volume visualization free of visual clutter and occlusion. Interactively computing DVLs is challenging when the data is large, and the volume grid is not structured/regular, as is often the case with computational fluid dynamics simulations. We extend DVLs to support large-scale, multifield adaptive mesh refinement (AMR) data that can be explored interactively. Our GPU-based system updates the DVL representation whenever the data or the alpha transfer function changes. We demonstrate and evaluate our interactive prototype using large AMR volumes from astrophysics simulations.
Open Access
Visualization of large Non-trivially partitioned unstructured data with native distribution on high-performance computing systems
(IEEE, 2024-01-15) Sahistan, Alper; Demirci, Serkan; Wald, Ingo; Zellmann, Stefan; Barbosa, João; Morrical, Nate; Güdükbay, Uğur
Interactively visualizing large finite element simulation data on High-Performance Computing (HPC) systems poses several difficulties. Some of these relate to unstructured data, which, even on a single node, is much more expensive to render compared to structured volume data. Worse yet, in the data parallel rendering context, such data with highly non-convex spatial domain boundaries will cause rays along its silhouette to enter and leave a given rank's domains at different distances. This straddling, in turn, poses challenges for both ray marching, which usually assumes successive elements to share a face, and compositing, which usually assumes a single fragment per pixel per rank. We holistically address these issues using a combination of three inter-operating techniques: first, we use a highly optimized GPU ray marching technique that, given an entry point, can march a ray to its exit point with highperformance by exploiting an exclusive-or (XOR) based compaction scheme. Second, we use hardware-accelerated ray tracing to efficiently find the proper entry points for these marching operations. Third, we use a “deep” compositing scheme to properly handle cases where different ranks' ray segments interleave in depth. We use GPU-to-GPU remote direct memory access (RDMA) to achieve interactive frame rates of 10-15 frames per second and higher for our motivating use case, the Fun3D NASA Mars Lander.