REAL-TIME ARBITRARY VIEW RENDERING ON GPU FROM STEREO VIDEO AND TIME-OF-FLIGHT CAMERA

Date

2011-05-18

Author

Ates, Tugrul K.
Alatan, Abdullah Aydın

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

156
views

0
downloads

Generating in-between images from multiple views of a scene is a crucial task for both computer vision and computer graphics fields. Photorealistic rendering, 3DTV and robot navigation are some of many applications which benefit from arbitrary view synthesis, if it is achieved in real-time. GPUs excel in achieving high computation power by processing arrays of data in parallel, which make them ideal for real-time computer vision applications. This paper proposes an arbitrary view rendering algorithm by using two high resolution color cameras along with a single low resolution time-of-flight depth camera and utilizing GPUs to achieve realtime processing rates. The presented ideas are examined in an experimental framework and based on the experimental results, it could be concluded that it is possible to realize content production and display stages of a free-viewpoint system in real-time by using only low-cost commodity computing devices.

Subject Keywords

FTV, TOF, Time-of-flight, GPU, Graphics processing unit, Image based rendering, Video plus depth, Bilateral filtering

URI

https://hdl.handle.net/11511/52546

Collections

Department of Electrical and Electronics Engineering, Conference / Seminar

Suggestions

OpenMETU
Core

Real-time arbitrary view rendering from stereo video and time-of-flight camere Ateş, Tuğrul Kağan; Alatan, Abdullah Aydın; Department of Electrical and Electronics Engineering (2010) Generating in-between images from multiple views of a scene is a crucial task for both computer vision and computer graphics fields. Photorealistic rendering, 3DTV and robot navigation are some of many applications which benefit from arbitrary view synthesis, if it is achieved in real-time. Most modern commodity computer architectures include programmable processing chips, called Graphics Processing Units (GPU), which are specialized in rendering computer generated images. These devices excel in achieving h...
Voxel transformation: scalable scene geometry discretization for global illumination Yalciner, Bora; Sahillioğlu, Yusuf (Springer Science and Business Media LLC, 2020-10-01) In real-time computer graphics, efficient discretization of scenes is required in order to accelerate graphics related algorithms such as realistic rendering with indirect illumination and visibility checking. Sparse voxel octree (SVO) is a popular data structure for such a discretization task. Populating an SVO with data is challenging when dynamic object count is high, especially when data per spatial location is large. Problem of populating such trees is adressed with our Voxel Transformation method, whe...
DATA-DRIVEN IMAGE CAPTIONING WITH META-CLASS BASED RETRIEVAL Kilickaya, Mert; Erdem, Erkut; Erdem, Aykut; İKİZLER CİNBİŞ, NAZLI; Çakıcı, Ruket (2014-04-25) Automatic image captioning, the process cif producing a description for an image, is a very challenging problem which has only recently received interest from the computer vision and natural language processing communities. In this study, we present a novel data-driven image captioning strategy, which, for a given image, finds the most visually similar image in a large dataset of image-caption pairs and transfers its caption as the description of the input image. Our novelty lies in employing a recently' pr...
Image compression method based on learned lifting-based dwt and learned zerotree-like entropy model Şahin, Uğur Berk; Kamışlı, Fatih; Department of Electrical and Electronics Engineering (2022-8) The success of deep learning in computer vision has sparked great interest in investigating deep learning-based algorithms also in many image processing applications, including image compression. The most popular end-to-end learned image compression approaches are based on auto-encoder architectures, where the image is mapped via convolutional neural networks (CNNs) into a transform (latent) representation that is quantized and processed again with CNNs to obtain the reconstructed image. The quantized laten...
3D Planar Representation of Stereo Depth Images for 3DTV Applications Ozkalayci, Burak O.; Alatan, Abdullah Aydın (2014-12-01) The depth modality of the multiview video plus depth (MVD) format is an active research area, whose main objective is to develop depth image based rendering friendly efficient compression methods. As a part of this research, a novel 3D planar-based depth representation is proposed. The planar approximation of multiple depth images are formulated as an energy-based co-segmentation problem by a Markov random field model. The energy terms of this problem are designed to mimic the rate-distortion tradeoff for a...

Citation Formats

T. K. Ates and A. A. Alatan, “REAL-TIME ARBITRARY VIEW RENDERING ON GPU FROM STEREO VIDEO AND TIME-OF-FLIGHT CAMERA,” 2011, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/52546.