Light-field (LF) is foreseen as an enabler for the next generation of 3D/AR/VR experiences. However, lack of unified representation, storage and processing formats, variant LF acquisition systems and capture-specific LF processing algorithms prevent cross-platform approaches and constrain the advancement and standardization process of the LF information. In this…
research Paper / Apr 2024 / Compression, Volumetric Imaging, Machine learning/ Deep learning /Artificial Intelligence
"Learning-based point cloud (PC) compression is a promising research avenue to reduce the transmission and storage costs for PC applications. Existing learning-based methods to compress PCs attributes employ variational autoencoders (VAE) or normalizing flows (NF) to learn compact signal representations. However, VAEs leverage a lower-dimensional bottleneck that…
360° video, supporting the ability to present views consistent with the rotation of the viewer's head along three axes (roll, pitch, yaw) is the current approach for creation of immersive video experiences. Nevertheless, a more fully natural, photorealistic experience - with support of visual cues that facilitate coherent psycho-visual sensory fusion without the…
Representation of 3D scenes is gaining popularity in industry, notably for Virtual Reality, Augmented Reality, and 360° Video. The point cloud format is well suited for such representations. Indeed, point clouds can be created with a simple capture process and modest processing, enabling a real-time, end-to-end point cloud distribution chain. However, point clou…
research Paper / Mar 2024 / Volumetric Imaging, Machine learning/ Deep learning /Artificial Intelligence
The universality of the point cloud format enables many 3D applications, making the compression of point clouds a critical phase in practice. Sampled as discrete 3D points, a point cloud approximates 2D surface(s) embedded in 3D with a finite bit-depth. However, the point distribution of a practical point cloud changes drastically as its bit-depth increases, req…
Representation of 3D scenes is gaining popularity in industry, notably for Virtual Reality, Augmented Reality, and 360° Video. The point cloud format is well suited for such representations. Indeed, point clouds can be created with a simple capture process and modest processing, enabling a real-time, end-to-end point cloud distribution chain. However, point clou…
Recent years have shown significant advances in immersive media experiences. Three-dimensional representation formats allow for new forms of entertainment and communication. In this context, point cloud data has emerged as a promising enabler for such experiences. Because efficient enough point cloud compression technologies are still to be found, the Moving Pic…
The quantity and diversity of data in Light-Field videos makes this content valuable for many applications such as mixed and augmented reality or post-production in the movie industry. Some of such applications require a large parallax between the different views of the Light-Field, making the multi-view capture a better option than plenoptic cameras. In this pa…
research Paper / Jan 2022 / Immersive / AR/VR/MR, Light Field, Volumetric Imaging, Machine learning/ Deep learning /Artificial Intelligence
Recently, learning methods have been designed to create Multiplane Images (MPIs) for view synthesis. While MPIs are extremely powerful and facilitate high quality renderings, a great amount of memory is required, making them impractical for many applications. In this paper, we propose a learning method that optimizes the available memory to render compact and ad…
research Paper / Dec 2020 / Volumetric Imaging, Machine learning/ Deep learning /Artificial Intelligence
We present a novel learning-based approach to synthesize new views of a light field image. In particular, given the four corner views of a light field, the presented method estimates any in-between view. We use three sequential convolutional neural networks for feature extraction, scene geometry estimation and view selection. Compared to state-of-the-art approac…
Light field acquisition devices allow capturing scenes with unmatched postprocessing possibilities. However, the huge amount of high-dimensional data poses challenging problems to light field processing in interactive time. In order to enable light field processing with a tractable complexity, in this paper, we address the problem of light field oversegmentation…
Presentation of Light Fields pipeline for Immersive Video Experiences
In this paper, we present a complete processing pipeline for focused plenoptic cameras. In particular, we propose 1) a new algorithm for microlens center calibration fully in the Fourier domain, 2) a novel algorithm for depth map computation using a stereo focal stack, and 3) a depth-based rendering algorithm that is able to refocus at a particular depth or to c…
In this paper, we introduce a novel graph representation forinteractive light field segmentation using Markov Random Field (MRF).The greatest barrier to the adoption of MRF for light field processing isthe large volume of input data. The proposed graph structure exploits theredundancy in the ray space in order to reduce the graph size, decreasingthe running time…
"This document gives an overview of the V3C Immersive Platform delivered to the Reference Tools 5G MAG An item ""V3C Immersive Platform"" will be added to the page https://5g-mag.github.io/Getting-Started/"