Traditional holographic printing techniques prove inadequate when only input data are available. Therefore, this paper proposes a new artificial-intelligence-based process for generating digital holographic stereograms from a single black-and-white p...
Nowadays, we are witnessing the wide diffusion of active depth sensors. However, the generalization capabilities and performance of the deep face recognition approaches that are based on depth data are hindered by the different sensor technologies an...
When it comes to evaluating perceptual quality of digital media for overall quality of experience assessment in immersive video applications, typically two main approaches stand out: Subjective and objective quality evaluation. On one hand, subjectiv...
This paper presents a new approach for fall detection from partially-observed depth-map video sequences. The proposed approach utilizes the 3D skeletal joint positions obtained from the Microsoft Kinect sensor to build a view-invariant descriptor for...
The capsule endoscopy robot can only use monocular vision due to the dimensional limit. To improve the depth perception of the monocular capsule endoscopy robot, this paper proposes a photometric stereo-based depth map reconstruction method. First, b...
As one of the key requirements for underwater exploration, underwater depth map estimation is of great importance in underwater vision research. Although significant progress has been achieved in the fields of image-to-image translation and depth map...
Current depth map sensing technologies capture depth maps at low spatial resolution, rendering serious problems in various applications. In this paper, we propose a single depth map super-resolution method that combines the advantages of model-based...
Color images have long been used as an important supplementary information to guide the super-resolution of depth maps. However, how to quantitatively measure the guiding effect of color images on depth maps has always been a neglected issue. To solv...
Deep map prediction plays a crucial role in comprehending the three-dimensional structure of a scene, which is essential for enabling mobile robots to navigate autonomously and avoid obstacles in complex environments. However, most existing depth est...
Depth maps obtained through sensors are often unsatisfactory because of their low-resolution and noise interference. In this paper, we propose a real-time depth map enhancement system based on a residual network which uses dual channels to process de...
Depth map super-resolution (DSR) is a technique aimed at restoring high-resolution (HR) depth maps from low-resolution (LR) depth maps. In this process, color images are commonly used as guidance to enhance the restoration procedure. However, the int...
In this paper, we propose a novel model to extract highly precise depth maps from missing viewpoints, especially for generating holographic 3D content. These depth maps are essential elements for phase extraction, which is required for the synthesis...
Multiple description (MD) coding is a promising alternative for the robust transmission of information over error-prone channels. In 3D image technology, the depth map represents the distance between the camera and objects in the scene. Using the dep...
In order to avoid the direct depth reconstruction of the original image pair and improve the accuracy of the results, we proposed a coarse-to-fine stereo matching network combining multi-level residual optimization and depth map super-resolution (ASR...
In this paper, we propose a method to refine the depth maps obtained by Multi-View Stereo (MVS) through iterative optimization of the Neural Radiance Field (NeRF). MVS accurately estimates the depths on object surfaces, and NeRF accurately estimates...
Depth maps captured by traditional consumer-grade depth cameras are often noisy and low-resolution. Especially when upsampling low-resolution depth maps with large upsampling factors, the resulting depth maps tend to suffer from vague edges. To addre...
Converting the actual scenes into three-dimensional models has inevitably become one of the fundamental requirements in autonomous driving. At present, the main obstacle to large-scale deployment is the high-cost lidar for environment sensing. Monocu...
The abundant visual information contained in multi-view images is widely used in computer vision tasks. Existing visual relationship detection frameworks have extended the feature vector to improve model performance. However, single view information...
Scene depth information is a key component of any robotic mobile application. Range sensors, such as LiDAR, sonar, or radar, capture depth data of a scene. However, the data captured by these sensors frequently presents missing regions or information...
Depth images obtained from lightweight, real-time depth estimation models and consumer-oriented sensors typically have low-resolution issues. Traditional interpolation methods for depth image up-sampling result in a significant information loss, espe...
We designed an end-to-end dual-branch residual network architecture that inputs a low-resolution (LR) depth map and a corresponding high-resolution (HR) color image separately into the two branches, and outputs an HR depth map through a multi-scale,...
The new generation of 3D video is an international frontier research hotspot. However, the large amount of data and high complexity are core problems to be solved urgently in 3D video coding. The latest generation of video coding standard versatile v...
Efficient intra-mode decision for depth maps assumes a pivotal role in augmenting the overall performance of 3D-HEVC. Existing research endeavors predominantly rely on fast mode screening strategies grounded in texture characteristics or machine lear...
As many new coding techniques and coding structures have been introduced to further improve the coding efficiency of depth maps in 3D video extensions, the coding complexity has been greatly increased. Fast algorithms are now needed to improve coding...
Three-Dimensional High-Efficiency Video Coding (3D-HEVC) efficiently compresses 3D video by incorporating depth map encoding techniques. However, the quadtree partitioning of depth map coding units (CUs) greatly increases computational complexity, co...
We present a new approach for a surface characterization based on the TIE method combined with the SEM. Experimental verification is carried out on the example of characterization of a crater on the surface of monocrystalline silicon (111). The appro...
Reconstructing 3D objects from single-view images has acquired significant interest due to their wide-ranging applications in robotics, autonomous vehicles, virtual reality, and augmented reality. Current methods, including voxel-based and point clou...
Three-Dimensional High-Efficiency Video Coding (3D-HEVC) has been extensively researched due to its efficient compression and deep image representation, but encoding complexity continues to pose a difficulty. This is mainly attributed to redundancy i...
In the depth map obtained through binocular stereo matching, there are many ill regions due to reasons such as lighting or occlusion. These ill regions cannot be accurately obtained due to the lack of information required for matching. Since the comp...
Face verification is the task of checking if two provided images contain the face of the same person or not. In this work, we propose a fully-convolutional Siamese architecture to tackle this task, achieving state-of-the-art results on three publicly...
The Microsoft HoloLens is a head-worn mobile augmented reality device that is capable of mapping its direct environment in real-time as triangle meshes and localize itself within these three-dimensional meshes simultaneously. The device is equipped w...
In this paper, we propose a multi-modal 2D + 3D face recognition method for a smart city application based on a Wireless Sensor Network (WSN) and various kinds of sensors. Depth maps are exploited for the 3D face representation. As for feature extrac...
In this paper, we propose a novel 2D-to-3D video conversion method for 3D entertainment applications. 3D entertainment is getting more and more popular and can be found in many contexts, such as TV and home gaming equipment. 3D image sensors are a n...
This paper proposes an action recognition framework for depth map sequences using the 3D Space-Time Auto-Correlation of Gradients (STACOG) algorithm. First, each depth map sequence is split into two sets of sub-sequences of two different frame length...
To determine which interpolation technique is the most suitable for each case study is an essential task for a correct soil mapping, particularly in studies performed at a regional scale. So, our main goal was to identify the most accurate method for...
Autonomous robots for smart homes and smart cities mostly require depth perception in order to interact with their environments. However, depth maps are usually captured in a lower resolution as compared to RGB color images due to the inherent limita...
In this paper, we introduce an approach for measuring human gait symmetry where the input is a sequence of depth maps of subject walking on a treadmill. Body surface normals are used to describe 3D information of the walking subject in each frame. Tw...
As a new generation 3D video coding standard, 3D-HEVC offers highly efficient compression. However, its recursive quadtree partitioning mechanism and frequent rate-distortion optimization (RDO) computations lead to a significant increase in coding co...
The identification of flood hazards during emerging public safety crises such as hurricanes or flash floods is an invaluable tool for first responders and managers yet remains out of reach in any comprehensive sense when using traditional remote-sens...
The field of mobile robotics has seen significant growth regarding the use of indoor laser mapping technology, but most two-dimensional Light Detection and Ranging (2D LiDAR) can only scan a plane of fixed height, and it is difficult to obtain the in...
The repeat acquisition of high-resolution snow depth measurements has important research and civil applications in the Arctic. Currently the surveying methods for capturing the high spatial and temporal variability of the snowpack are expensive, in p...
Applications such as medical diagnosis, navigation, robotics, etc., require 3D images. Recently, deep learning networks have been extensively applied to estimate depth. Depth prediction from 2D images poses a problem that is both ill–posed and...
Holographic display has the potential to be utilized in many 3D application scenarios because it provides all the depth cues that human eyes can perceive. However, the shortage of 3D content has limited the application of holographic 3D displays. To...
The Hashim Chalbi house, a historic private residence with notable architectural features located within Erbil Citadel—a UNESCO World Heritage site since 2014—was turned into a museum. This study utilizes space syntax analysis (depth maps...
We present Stereo-GS, a real-time system for online 3D Gaussian Splatting (3DGS) that reconstructs photorealistic 3D scenes from streaming stereo pairs. Unlike prior offline 3DGS methods that require dense multi-view input or precomputed depth, Stere...
Owing to the low detection accuracy of camera-based object detection models, various fusion techniques with Light Detection and Ranging (LiDAR) have been attempted. This has resulted in improved detection of objects that are difficult to detect due t...
A rapid development and growing popularity of additive manufacturing technology leads to new challenging tasks allowing not only a reliable monitoring of the progress of the 3D printing process but also the quality of the printed objects. The automat...
23 September 2022
Addressing the problems facing the elderly, whether living independently or in managed care facilities, is considered one of the most important applications for action recognition research. However, existing systems are not ready for automation, or f...
To address the problem caused by mixed pixels in MODIS images for high-resolution crop mapping, this paper presents a novel spatial–temporal deep learning-based approach for sub-pixel mapping (SPM) of different crop types within mixed pixels fr...
Finding depth information with stereo matching using a deep learning algorithm for embedded systems has recently gained significant attention owing to emerging high-performance mobile graphics processing units (GPUs). Several researchers have propose...
of 76