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Journal articles on the topic '3D Depth Model'

Author: Grafiati

Published: 1 April 2023

Last updated: 31 July 2025

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1

Mukhtar, N. F., S. Azri, U. Ujang, M. G. Cuétara, G. M. Retortillo, and S. Mohd Salleh. "3D MODEL FOR INDOOR SPACES USING DEPTH SENSOR." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-4/W16 (October 1, 2019): 471–79. http://dx.doi.org/10.5194/isprs-archives-xlii-4-w16-471-2019.

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Abstract. In recent years, 3D model for indoor spaces have become highly demanded in the development of technology. Many approaches to 3D visualisation and modelling especially for indoor environment was developed such as laser scanner, photogrammetry, computer vision, image and many more. However, most of the technique relies on the experience of the operator to get the best result. Besides that, the equipment is quite expensive and time-consuming in terms of processing. This paper focuses on the data acquisition and visualisation of a 3D model for an indoor space by using a depth sensor. In

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Lü, Qingtian, Guang Qi, and Jiayong Yan. "3D geologic model of Shizishan ore field constrained by gravity and magnetic interactive modeling: A case history." GEOPHYSICS 78, no. 1 (2013): B25—B35. http://dx.doi.org/10.1190/geo2012-0126.1.

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We performed a study on using an integrated geologic model in mineral exploration at depth. Shizishan ore field, in the western part of the Tongling ore district, Anhui Province in China, is well known for its polymetallic deposits and recent deep discovery of Dongguashan deposit at around 1000-m depth. Understanding the 3D structure and delineating the locations and variations of the intrusions and ore-controlling strata in the study area are essential for selecting deep mineral targets. A pilot 3D geologic model, covering an area of 11 × 16 km and extends to a depth of 3 km, has been constru

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Liu, Yong Guang, Ming Quan Zhou, and Ya Chun Fan. "Using Depth Image in 3D Model Retrieval System." Advanced Materials Research 268-270 (July 2011): 981–87. http://dx.doi.org/10.4028/www.scientific.net/amr.268-270.981.

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For content-based 3D model retrieval, an improved depth image-based feature extraction algorithm is proposed. First, a 3-D model is preprocessed. Secondly, six depth images are generated in three principal directions in the normalized coordinate system. Thirdly, the eigenvectors of 3D model are obtained through 2D Fourier Transform of the depth images. Finally a new method is used for low-frequency sampling. Experiments show that the approach performed quite well despite its apparently simple approach. In our large 3D database, our approach is well for variant resolution models and holds satis

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Zhang, Huang, and Zhao. "A New Model of RGB-D Camera Calibration Based On 3D Control Field." Sensors 19, no. 23 (2019): 5082. http://dx.doi.org/10.3390/s19235082.

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With extensive application of RGB-D cameras in robotics, computer vision, and many other fields, accurate calibration becomes more and more critical to the sensors. However, most existing models for calibrating depth and the relative pose between a depth camera and an RGB camera are not universally applicable to many different kinds of RGB-D cameras. In this paper, by using the collinear equation and space resection of photogrammetry, we present a new model to correct the depth and calibrate the relative pose between depth and RGB cameras based on a 3D control field. We establish a rigorous re

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Kwon, Ki Hoon, Munkh-Uchral Erdenebat, Nam Kim, et al. "High-Quality 3D Visualization System for Light-Field Microscopy with Fine-Scale Shape Measurement through Accurate 3D Surface Data." Sensors 23, no. 4 (2023): 2173. http://dx.doi.org/10.3390/s23042173.

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We propose a light-field microscopy display system that provides improved image quality and realistic three-dimensional (3D) measurement information. Our approach acquires both high-resolution two-dimensional (2D) and light-field images of the specimen sequentially. We put forward a matting Laplacian-based depth estimation algorithm to obtain nearly realistic 3D surface data, allowing the calculation of depth data, which is relatively close to the actual surface, and measurement information from the light-field images of specimens. High-reliability area data of the focus measure map and spatia

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Zhang, Fan, Junli Zhao, Liang Wang, and Fuqing Duan. "3D Face Model Super-Resolution Based on Radial Curve Estimation." Applied Sciences 10, no. 3 (2020): 1047. http://dx.doi.org/10.3390/app10031047.

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Consumer depth cameras bring about cheap and fast acquisition of 3D models. However, the precision and resolution of these consumer depth cameras cannot satisfy the requirements of some 3D face applications. In this paper, we present a super-resolution method for reconstructing a high resolution 3D face model from a low resolution 3D face model acquired from a consumer depth camera. We used a group of radial curves to represent a 3D face. For a given low resolution 3D face model, we first extracted radial curves on it, and then estimated their corresponding high resolution ones by radial curve

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Sintunata, Vicky, and Terumasa Aoki. "Color Segmentation Based Depth Adjustment for 3D Model Reconstruction from a Single Input Image." International Journal of Computer Theory and Engineering 8, no. 2 (2016): 171–76. http://dx.doi.org/10.7763/ijcte.2016.v8.1039.

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Hollands, J. G., Heather A. Parker, and Andrew Morton. "Judgments of 3D Bars in Depth." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 46, no. 17 (2002): 1565–69. http://dx.doi.org/10.1177/154193120204601708.

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Twenty participants judged the relative size of two bars portrayed at different locations in a 3D bar graph. Bars were co-located, placed side by side (near adjacent), or the small bar occluded the large (near or far occluded). Error was greater for the far occluded condition and there was greater variability in bias scores. To account for observed error, we proposed a model that distinguishes between cyclical bias commonly observed in proportion judgments and bias resulting from improper size-distance scaling. The model was fit to data, and the results indicated that the absolute value of siz

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Magistrale, Harold, Keith McLaughlin, and Steven Day. "A geology-based 3D velocity model of the Los Angeles basin sediments." Bulletin of the Seismological Society of America 86, no. 4 (1996): 1161–66. http://dx.doi.org/10.1785/bssa0860041161.

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Abstract Seismic hazard studies of the Los Angeles basin area require a realistic seismic-velocity model. We use geologic information about depth to crystalline basement, depths to sedimentary horizons, uplift of sediments, and surface geology in a velocity-depth-age function to construct a three-dimensional velocity model. In earthquake location tests, the model predicts travel times satisfactorily, and in earthquake ground-motion simulations, the model correctly determines the timing and amplitude of late-arriving waves.

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Wu, Di, Xudong Zhang, Jun Zhang, Zhiguo Fan, and Rui Sun. "Light field depth estimation guided by 3D occlusion model." Journal of Image and Graphics 26, no. 4 (2021): 924–38. http://dx.doi.org/10.11834/jig.200131.

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Zhang, X. Y., B. Zhou, H. Li, and W. Xin. "Depth detection of spar cap defects in large-scale wind turbine blades based on a 3D heat conduction model using step heating infrared thermography." Measurement Science and Technology 33, no. 5 (2022): 055008. http://dx.doi.org/10.1088/1361-6501/ac41a8.

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Abstract The defects dispersed in a spar cap often lead to the failure of large-scale wind turbine blades. To predict the residual service life of the blade and make the repair, it is necessary to detect the depth of spar cap defects. Step-heating thermography (SHT) is a common infrared technique in this domain. However, the existing methods of SHT on defect depth detection are generally based on 1D models, which are unable to accurately detect the depth of spar cap defects due to ignoring material anisotropy and in-plane heat flow. To improve the depth detection accuracy of spar cap defects,

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Wang, Zhijian, Jie Liu, Yixiao Sun, et al. "Applying auxiliary supervised depth-assisted transformer and cross modal attention fusion in monocular 3D object detection." PeerJ Computer Science 11 (January 28, 2025): e2656. https://doi.org/10.7717/peerj-cs.2656.

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Monocular 3D object detection is the most widely applied and challenging solution for autonomous driving, due to 2D images lacking 3D information. Existing methods are limited by inaccurate depth estimations by inequivalent supervised targets. The use of both depth and visual features also faces problems of heterogeneous fusion. In this article, we propose Depth Detection Transformer (Depth-DETR), applying auxiliary supervised depth-assisted transformer and cross modal attention fusion in monocular 3D object detection. Depth-DETR introduces two additional depth encoders besides the visual enco

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Zhang, Qiuwen, Liang Tian, Lixun Huang, Xiaobing Wang, and Haodong Zhu. "Rendering Distortion Estimation Model for 3D High Efficiency Depth Coding." Mathematical Problems in Engineering 2014 (2014): 1–7. http://dx.doi.org/10.1155/2014/940737.

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A depth map represents three-dimensional (3D) scene geometry information and is used for depth image based rendering (DIBR) to synthesize arbitrary virtual views. Since the depth map is only used to synthesize virtual views and is not displayed directly, the depth map needs to be compressed in a certain way that can minimize distortions in the rendered views. In this paper, a modified distortion estimation model is proposed based on view rendering distortion instead of depth map distortion itself and can be applied to the high efficiency video coding (HEVC) rate distortion cost function proces

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A.R., Mrs Kamble,. "Implementation Paper on Automated 2D Image to 3D Model Generation." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 05 (2024): 1–5. http://dx.doi.org/10.55041/ijsrem34995.

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With the rise of digital world, traditional learning methods, while time-tested, often fall short in meeting the dynamic educational needs of today’s learners. They are constrained by several drawbacks that impede effective comprehension and engagement. This abstract sheds light on the limitations of traditional learning approaches and introduces how the integration of 3D model reconstruction can mitigate these challenges, thereby enhancing the learning experience. We proposed deep Conventional techniques, which create a virtual view from a reference picture, use two distinct steps: depth imag

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A.R, Prof Kamble. "A Survey on Automated 2D Image to 3D Model Generation." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 04 (2024): 1–5. http://dx.doi.org/10.55041/ijsrem31226.

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With the rise of digital world, Traditional learning methods, while time-tested, often fall short in meeting the dynamic educational needs of today’s learners. They are constrained by several drawbacks that impede effective comprehension and engagement. This abstract sheds light on the limitations of traditional learning approaches and introduces how the integration of 3D model reconstruction can mitigate these challenges, thereby enhancing the learning experience. We proposed deep Conventional techniques, which create a virtual view from a reference picture, use two distinct steps: depth imag

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Valdez-Rodríguez, José E., Hiram Calvo, Edgardo Felipe-Riverón, and Marco A. Moreno-Armendáriz. "Improving Depth Estimation by Embedding Semantic Segmentation: A Hybrid CNN Model." Sensors 22, no. 4 (2022): 1669. http://dx.doi.org/10.3390/s22041669.

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Single image depth estimation works fail to separate foreground elements because they can easily be confounded with the background. To alleviate this problem, we propose the use of a semantic segmentation procedure that adds information to a depth estimator, in this case, a 3D Convolutional Neural Network (CNN)—segmentation is coded as one-hot planes representing categories of objects. We explore 2D and 3D models. Particularly, we propose a hybrid 2D–3D CNN architecture capable of obtaining semantic segmentation and depth estimation at the same time. We tested our procedure on the SYNTHIA-AL d

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Ngo, Duc Tuan, Minh-Quan Viet Bui, Duc Dung Nguyen, and Hoang-Anh Pham. "eGAC3D: enhancing depth adaptive convolution and depth estimation for monocular 3D object pose detection." PeerJ Computer Science 8 (November 3, 2022): e1144. http://dx.doi.org/10.7717/peerj-cs.1144.

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Many alternative approaches for 3D object detection using a singular camera have been studied instead of leveraging high-precision 3D LiDAR sensors incurring a prohibitive cost. Recently, we proposed a novel approach for 3D object detection by employing a ground plane model that utilizes geometric constraints named GAC3D to improve the results of the deep-based detector. GAC3D adopts an adaptive depth convolution to replace the traditional 2D convolution to deal with the divergent context of the image’s feature, leading to a significant improvement in both training convergence and testing accu

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Yu, Jongsub, and Hyukdoo Choi. "YOLO MDE: Object Detection with Monocular Depth Estimation." Electronics 11, no. 1 (2021): 76. http://dx.doi.org/10.3390/electronics11010076.

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This paper presents an object detector with depth estimation using monocular camera images. Previous detection studies have typically focused on detecting objects with 2D or 3D bounding boxes. A 3D bounding box consists of the center point, its size parameters, and heading information. However, predicting complex output compositions leads a model to have generally low performances, and it is not necessary for risk assessment for autonomous driving. We focused on predicting a single depth per object, which is essential for risk assessment for autonomous driving. Our network architecture is base

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Maulahikmah, Galinium, Yapri Jason, and Purnama James. "Markerless motion capture for 3D human model animation using depth camera." TELKOMNIKA Telecommunication, Computing, Electronics and Control 17, no. 3 (2019): 1300–1309. https://doi.org/10.12928/TELKOMNIKA.v17i3.8939.

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3D animation is created using keyframe based system in 3D animation software such as Blender and Maya. Due to the long time interval and the need of high expertise in 3D animation, motion capture devices were used as an alternative and Microsoft Kinect v2 sensor is one of them. This research analyses the capabilities of the Kinect sensor in producing 3D human model animations using motion capture and keyframe based animation system in reference to a live motion performance. The quality, time interval and cost of both animation results were compared. The experimental result shows that motion ca

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Wang, Hongwei, Jie Gao, and Jingjing Liu. "Research and Implementation of the Sports Analysis System Based on 3D Image Technology." Wireless Communications and Mobile Computing 2021 (October 6, 2021): 1–11. http://dx.doi.org/10.1155/2021/4266417.

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On the basis of existing research, this paper analyzes the algorithms and technologies of 3D image-based sports models in depth and proposes a fusion depth map in view of some of the shortcomings of the current hot spot sports model methods based on 3D images. We use the 3D space to collect the depth image, remove the background from the depth map, recover the 3D motion model from it, and then build the 3D model database. In this paper, based on the characteristics of continuity in space and smoothness in time of a rigid body moving target, a reasonable rigid body target motion hypothesis is p

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Wang, Rui, Bo Liu, Zhikang Li, Hao Yi, Zeyu Guo, and Zhen Chen. "Bayesian Model for 3D Undulating Terrain Depth Estimation Using Photon Counting LiDAR." Remote Sensing 15, no. 19 (2023): 4719. http://dx.doi.org/10.3390/rs15194719.

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Photon counting LiDAR can capture the 3D information of long-distance targets and has the advantages of high sensitivity and high resolution. However, the noise counts restrict improvements in the photon counting imaging quality. Therefore, how to make full use of the limited signal counts under noise interference to achieve efficient 3D imaging is one of the main problems in current research. To address this problem, in this paper, we proposes a 3D imaging method for undulating terrain depth estimation that combines constant false alarm probability detection with the Bayesian model. First, th

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Truong Giang, Khang, Soohwan Song, Daekyum Kim, and Sunghee Choi. "Sequential Depth Completion With Confidence Estimation for 3D Model Reconstruction." IEEE Robotics and Automation Letters 6, no. 2 (2021): 327–34. http://dx.doi.org/10.1109/lra.2020.3043172.

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Wang, Mei, Ruizhuo Xu, Weihong Deng, and Hua Huang. "Implicit face model: Depth super-resolution for 3D face recognition." Pattern Recognition 162 (June 2025): 111353. https://doi.org/10.1016/j.patcog.2025.111353.

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HASSAN, Ahmed Gamal Mohamed, and Karam Samir Ibrahim FARAG. "Multi-stage 3D Gravity Inversion Scheme for Maximum Optimization of the Subsurface Basement Model at Gebel El-Zeit Basin, Southwestern Gulf-of-Suez, Egypt." NEWS of the Ural State Mining University, no. 4 (December 15, 2023): 19–39. http://dx.doi.org/10.21440/2307-2091-2023-4-19-39.

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Relevance and purpose of the work. Due to its basement fault block pattern in the sedimentary basin, the Southwestern Gulf of Suez’s Gebel El-Zeit basin is one of Egypt’s most desirable hydrocarbon concessions. However, salt diapers in sedimentary layers have hindered seismic interpretations in this area, making it challenging to build a 3D central primary basinal structure. This study uses Bouguer gravity anomalies to input basement complex lateral density model assumptions to determine the optimal three-dimensional basement depth for the study area. Research methodology. Based on the concept

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Irawan, Jefri Bambang, and Wahyu Triyoso. "3D Check shot Modeling for Time-Depth Conversion." IOP Conference Series: Earth and Environmental Science 1227, no. 1 (2023): 012018. http://dx.doi.org/10.1088/1755-1315/1227/1/012018.

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Abstract Time-depth conversion is one of the keys to successful drilling with a specific target. However, if the drilling target is incorrectly defined, it can cause significant material losses. For example, several cases found that the hydrocarbon depth was deeper than the expected target. As a result, the well will be considered dry even though it still has hydrocarbon reserves. In this study, we intend to develop 3D check shot modeling in which check shot and formation marker data are referred to and taken at the well to obtain a precise time-depth relationship to overcome this problem. The

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Freer, JJ, GA Tarling, MA Collins, JC Partridge, and MJ Genner. "Estimating circumpolar distributions of lanternfish using 2D and 3D ecological niche models." Marine Ecology Progress Series 647 (August 13, 2020): 179–93. http://dx.doi.org/10.3354/meps13384.

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Ecological niche models (ENMs) can be a practical approach for investigating distributions and habitat characteristics of pelagic species. In principle, to reflect the ecological niche of a species well, ENMs should incorporate environmental predictors that consider its full vertical habitat, yet examples of such models are rare. Here we present the first application of ‘3D’ ENMs to 10 Southern Ocean lanternfish species. This 3D approach incorporates depth-specific environmental predictor data to identify the distribution of suitable habitat across multiple depth levels. Results were compared

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Luijendijk, Arjen, Johan Henrotte, Dirk Jan Walstra, and Maarten Van Ormondt. "QUASI-3D MODELLING OF SURF ZONE DYNAMICS." Coastal Engineering Proceedings 1, no. 32 (2011): 52. http://dx.doi.org/10.9753/icce.v32.currents.52.

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A quasi-three-dimensional model (quasi-3D) has been developed through the implementation of an analytical 1DV flow model in existing depth-averaged shallow water equations. The model includes the effects of waves and wind on the vertical distribution of the horizontal velocities. Comparisons with data from both physical and field cases show that the quasi-3D approach is able to combine the effect of vertical structures with the efficiency of depth-averaged simulations. Inter-comparisons with three-dimensional simulations show that the quasi-3D approach can represent similar velocity prof

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Zhu, Chuanbin, Fabrice Cotton, and Marco Pilz. "Testing the Depths to 1.0 and 2.5 km/s Velocity Isosurfaces in a Velocity Model for Japan and Implications for Ground‐Motion Modeling." Bulletin of the Seismological Society of America 109, no. 6 (2019): 2710–21. http://dx.doi.org/10.1785/0120190016.

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Abstract In the Next Generation Attenuation West2 (NGA‐West2) project, a 3D subsurface structure model (Japan Seismic Hazard Information Station [J‐SHIS]) was queried to establish depths to 1.0 and 2.5 km/s velocity isosurfaces for sites without depth measurement in Japan. In this article, we evaluate the depth parameters in the J‐SHIS velocity model by comparing them with their corresponding site‐specific depth measurements derived from selected KiK‐net velocity profiles. The comparison indicates that the J‐SHIS model underestimates site depths at shallow sites and overestimates depths at dee

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Xu, Zhengze, and Wenjun Zhang. "3D CNN hand pose estimation with end-to-end hierarchical model and physical constraints from depth images." Neural Network World 33, no. 1 (2023): 35–48. http://dx.doi.org/10.14311/nnw.2023.33.003.

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Previous studies are mainly focused on the works that depth image is treated as flat image, and then depth data tends to be mapped as gray values during the convolution processing and features extraction. To address this issue, an approach of 3D CNN hand pose estimation with end-to-end hierarchical model and physical constraints is proposed. After reconstruction of 3D space structure of hand from depth image, 3D model is converted into voxel grid for further hand pose estimation by 3D CNN. The 3D CNN method makes improvements by embedding end-to-end hierarchical model and constraints algorithm

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Zhdanov, Michael S., Michael Jorgensen, and Le Wan. "Three-Dimensional Gravity Inversion in the Presence of the Sediment-Basement Interface: A Case Study in Utah, USA." Minerals 12, no. 4 (2022): 448. http://dx.doi.org/10.3390/min12040448.

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We introduce a novel approach to three-dimensional gravity inversion in the presence of the sediment-basement interface with a strong density contrast. This approach makes it possible to incorporate the known information about the basement depth in the inversion. It also allows the user to determine the depth-to-basement in the initial inversion phase. One can then use this interface to constrain the final inversion phase. First, the inversion generates the depth-to-basement model based on the 3D Cauchy-type integral representation of the gravity field. Then, in the second phase, full 3D voxel

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Korkalo, Otto, and Tapio Takala. "Measurement Noise Model for Depth Camera-Based People Tracking." Sensors 21, no. 13 (2021): 4488. http://dx.doi.org/10.3390/s21134488.

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Depth cameras are widely used in people tracking applications. They typically suffer from significant range measurement noise, which causes uncertainty in the detections made of the people. The data fusion, state estimation and data association tasks require that the measurement uncertainty is modelled, especially in multi-sensor systems. Measurement noise models for different kinds of depth sensors have been proposed, however, the existing approaches require manual calibration procedures which can be impractical to conduct in real-life scenarios. In this paper, we present a new measurement no

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H., Shalma, and Selvaraj P. "Structure tensor-based Gaussian kernel edge-adaptive depth map refinement with triangular point view in images." IAES International Journal of Artificial Intelligence (IJ-AI) 13, no. 2 (2024): 1945–53. https://doi.org/10.11591/ijai.v13.i2.pp1945-1953.

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Image reconstruction is the process of restoring the image resolution. In 3D image reconstruction, the objects in different viewpoints are processed with the triangular point view (TPV) method to estimate object geometry structure for 3D model. This work proposes a depth refinement methodology in preserving the geometric structure of objects using the structure tensor method with a Gaussian filter by transforming a series of 2D input images into a 3D model. The computation of depth map errors can be found by comparing the masked area/patch with the distribution of the original image's greyscal

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Khalili, Khalil, Seyed Yousef Ahmadi-Brooghani, and M. Rakhshkhorshid. "CAD Model Generation Using 3D Scanning." Advanced Materials Research 23 (October 2007): 169–72. http://dx.doi.org/10.4028/www.scientific.net/amr.23.169.

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3D Scanners are used in industrial applications such as reverse engineering and inspection. Customization of existing CAD systems is one of rapid ways to supplying a 3D Scanning software. In this paper, using AutoLisp and Visual Basic programming languages, AutoCAD has been customized. Also facilities of automatic scanning of physical parts, in the domain of free form surfaces, have been provided. Furthermore, possibilities such as, control of scanner automotive system, representation of registered point clouds, generation of polygon and /or NURBS model from primary or modified point clouds, h

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Kim, H., W. Yoon, and T. Kim. "AUTOMATED MOSAICKING OF MULTIPLE 3D POINT CLOUDS GENERATED FROM A DEPTH CAMERA." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B3 (June 9, 2016): 269–72. http://dx.doi.org/10.5194/isprs-archives-xli-b3-269-2016.

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In this paper, we propose a method for automated mosaicking of multiple 3D point clouds generated from a depth camera. A depth camera generates depth data by using ToF (Time of Flight) method and intensity data by using intensity of returned signal. The depth camera used in this paper was a SR4000 from MESA Imaging. This camera generates a depth map and intensity map of 176 x 44 pixels. Generated depth map saves physical depth data with mm of precision. Generated intensity map contains texture data with many noises. We used texture maps for extracting tiepoints and depth maps for assigning z c

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Kim, H., W. Yoon, and T. Kim. "AUTOMATED MOSAICKING OF MULTIPLE 3D POINT CLOUDS GENERATED FROM A DEPTH CAMERA." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B3 (June 9, 2016): 269–72. http://dx.doi.org/10.5194/isprsarchives-xli-b3-269-2016.

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In this paper, we propose a method for automated mosaicking of multiple 3D point clouds generated from a depth camera. A depth camera generates depth data by using ToF (Time of Flight) method and intensity data by using intensity of returned signal. The depth camera used in this paper was a SR4000 from MESA Imaging. This camera generates a depth map and intensity map of 176 x 44 pixels. Generated depth map saves physical depth data with mm of precision. Generated intensity map contains texture data with many noises. We used texture maps for extracting tiepoints and depth maps for assigning z c

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Pambudi, Doni Setio, and Lailatul Hidayah. "Foot 3D Reconstruction and Measurement using Depth Data." Journal of Information Systems Engineering and Business Intelligence 6, no. 1 (2020): 37. http://dx.doi.org/10.20473/jisebi.6.1.37-45.

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Background: The need for shoes with non-standard sizes is increasing, but this is not followed by the competence to measure the foot effectively. The high cost of such an instrument in the market has led to the development of a precise yet affordable measurement system.Objective: This research attempts to solve the measuring problem by employing an automatic instrument utilizing a depth image sensor that is available on the market at an affordable price.Methods: Data from several Realsense sensors that have been preprocessed are combined using transformation techniques and noise cleaning is pe

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Kwak, Jeonghoon, and Yunsick Sung. "Automatic 3D Landmark Extraction System Based on an Encoder–Decoder Using Fusion of Vision and LiDAR." Remote Sensing 12, no. 7 (2020): 1142. http://dx.doi.org/10.3390/rs12071142.

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To provide a realistic environment for remote sensing applications, point clouds are used to realize a three-dimensional (3D) digital world for the user. Motion recognition of objects, e.g., humans, is required to provide realistic experiences in the 3D digital world. To recognize a user’s motions, 3D landmarks are provided by analyzing a 3D point cloud collected through a light detection and ranging (LiDAR) system or a red green blue (RGB) image collected visually. However, manual supervision is required to extract 3D landmarks as to whether they originate from the RGB image or the 3D point c

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Cui, Meng-Yao, Shao-Ping Lu, Miao Wang, Yong-Liang Yang, Yu-Kun Lai, and Paul L. Rosin. "3D computational modeling and perceptual analysis of kinetic depth effects." Computational Visual Media 6, no. 3 (2020): 265–77. http://dx.doi.org/10.1007/s41095-020-0180-x.

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Abstract Humans have the ability to perceive kinetic depth effects, i.e., to perceived 3D shapes from 2D projections of rotating 3D objects. This process is based on a variety of visual cues such as lighting and shading effects. However, when such cues are weak or missing, perception can become faulty, as demonstrated by the famous silhouette illusion example of the spinning dancer. Inspired by this, we establish objective and subjective evaluation models of rotated 3D objects by taking their projected 2D images as input. We investigate five different cues: ambient luminance, shading, rotation

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Sun, Robert, George A. McMechan, Chen-Shao Lee, Jinder Chow, and Chen-Hong Chen. "Prestack scalar reverse-time depth migration of 3D elastic seismic data." GEOPHYSICS 71, no. 5 (2006): S199—S207. http://dx.doi.org/10.1190/1.2227519.

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Using two independent, 3D scalar reverse-time depth migrations, we migrate the reflected P- and S-waves in a prestack 3D, three-component (3-C), elastic seismic data volume generated with a P-wave source in a 3D model and recorded at the top of the model. Reflected P- and S-waves are extracted by divergence (a scalar) and curl (a 3-C vector) calculations, respectively, during shallow downward extrapolation of the elastic seismic data. The imaging time for the migrations of both the reflected P- and P-S converted waves at each point is the one-way P-wave traveltime from the source to that point

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Ma, Lan, and Hua Huo. "2D to 3D Human Skeleton Estimation Based on the Brown Camera Distortion Model and Constrained Optimization." Electronics 14, no. 5 (2025): 960. https://doi.org/10.3390/electronics14050960.

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In the rapidly evolving field of computer vision and machine learning, 3D skeleton estimation is critical for applications such as motion analysis and human–computer interaction. While stereo cameras are commonly used to acquire 3D skeletal data, monocular RGB systems attract attention due to benefits including cost-effectiveness and simple deployment. However, persistent challenges remain in accurately inferring depth from 2D images and reconstructing 3D structures using monocular approaches. The current 2D to 3D skeleton estimation methods overly rely on deep training of datasets, while negl

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Hu, Hui, Jianfeng Zhang, and Tao Li. "Dam-Break Flows: Comparison between Flow-3D, MIKE 3 FM, and Analytical Solutions with Experimental Data." Applied Sciences 8, no. 12 (2018): 2456. http://dx.doi.org/10.3390/app8122456.

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The objective of this study was to evaluate the applicability of a flow model with different numbers of spatial dimensions in a hydraulic features solution, with parameters such a free surface profile, water depth variations, and averaged velocity evolution in a dam-break under dry and wet bed conditions with different tailwater depths. Two similar three-dimensional (3D) hydrodynamic models (Flow-3D and MIKE 3 FM) were studied in a dam-break simulation by performing a comparison with published experimental data and the one-dimensional (1D) analytical solution. The results indicate that the Flo

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Shalma, H., and P. Selvaraj. "Structure tensor-based Gaussian kernel edge-adaptive depth map refinement with triangular point view in images." IAES International Journal of Artificial Intelligence (IJ-AI) 13, no. 2 (2024): 1945. http://dx.doi.org/10.11591/ijai.v13.i2.pp1945-1953.

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<span lang="EN-US">Image reconstruction is the process of restoring the image resolution. In 3D image reconstruction, the objects in different viewpoints are processed with the triangular point view (TPV) method to estimate object geometry structure for 3D model. This work proposes a depth refinement methodology in preserving the geometric structure of objects using the structure tensor method with a Gaussian filter by transforming a series of 2D input images into a 3D model. The computation of depth map errors can be found by comparing the masked area/patch with the distribution of the

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Bhargava Pananthula, Manoj Kumar. "3D Image Reconstruction from Single 2D Image using Deep Learning." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 04 (2025): 1–9. https://doi.org/10.55041/ijsrem44955.

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Abstract— Accurate 3D reconstruction from 2D images plays a critical role in various applications including medical imaging, robotics, autonomous navigation, and augmented reality. Traditional reconstruction techniques often require multiple viewpoints or sensor setups, limiting their feasibility in resource-constrained environments. In this work, we propose a deep learning-based monocular 3D reconstruction pipeline that generates high-quality 3D models from a single RGB image. The core of this framework lies in a custom U-Net++ architecture, designed and trained on the NYU Depth V2 dataset fo

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N., L. Manasa. "Addressing Latency Issues in 2D to 3D Conversion: Deploying Available Synthetic Database." International Journal of Informatics and Communication Technology (IJ-ICT) 7, no. 3 (2018): pp152–156. https://doi.org/10.11591/ijict.v7i3.pp152-156.

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Conventional 2D to 3D rendering techniques involve a sequential process of grouping of the input images based on edge information and predictive algorithms to assign depth values to pixels with same hue. The iterative calculations and volume of data under scrutiny to assign &bdquo;real-time" values raise latency issues and cost considerations. For commercial consumption, where speed and accuracy define the viability of a product, there is a need to reorient the approach used in the present methodologies. In predictive methodologies one of the core interests is achieving the initial approximati

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Visutsak, Porawat, Xiabi Liu, Chalothon Choothong, and Fuangfar Pensiri. "SIFT-Based Depth Estimation for Accurate 3D Reconstruction in Cultural Heritage Preservation." Applied System Innovation 8, no. 2 (2025): 43. https://doi.org/10.3390/asi8020043.

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This paper describes a proposed method for preserving tangible cultural heritage by reconstructing a 3D model of cultural heritage using 2D captured images. The input data represent a set of multiple 2D images captured using different views around the object. An image registration technique is applied to configure the overlapping images with the depth of images computed to construct the 3D model. The automatic 3D reconstruction system consists of three steps: (1) Image registration for managing the overlapping of 2D input images; (2) Depth computation for managing image orientation and calibra

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Kim, Hakdong, Heonyeong Lim, Minkyu Jee, Yurim Lee, MinSung Yoon, and Cheongwon Kim. "High-Precision Depth Map Estimation from Missing Viewpoints for 360-Degree Digital Holography." Applied Sciences 12, no. 19 (2022): 9432. http://dx.doi.org/10.3390/app12199432.

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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 of computer-generated holograms (CGHs). The proposed model, called the holographic dense depth, estimates depth maps through feature extraction, combining up-sampling. We designed and prepared a total of 9832 multi-view images with resolutions of 640 × 360. We evaluated our model by comparing the estimated depth maps with their ground truths using

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Ciobanu, Octavian. "Bioengineering Applications of 3D Scanning and Reconstruction Using a Depth Sensor." Applied Mechanics and Materials 809-810 (November 2015): 920–25. http://dx.doi.org/10.4028/www.scientific.net/amm.809-810.920.

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Paper approaches some characteristics and bioengineering applications of a handheld depth sensor for low-cost 3D scanning and reconstruction. The Kinect depth sensor used in this work was launched on June 2009 and was based around a gaming webcam peripheral. The Kinect sensor uses a structured light technique in order to develop real-time 3D surfaces. The 3D model of anatomic surface may have a lot of bioengineering applications. Some observations and comparisons are presented in connection with the scanning and 3D reconstruction of different anatomic surfaces.

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FANG Kai, 方恺. "Ecological footprint depth and size: new indicators for a 3D model." Acta Ecologica Sinica 33, no. 1 (2013): 267–74. http://dx.doi.org/10.5846/stxb201111051670.

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Galinium, Maulahikmah, Jason Yapri, and James Purnama. "27markerless motion capture for 3D human model animation using depth camera." TELKOMNIKA (Telecommunication Computing Electronics and Control) 17, no. 3 (2019): 1300. http://dx.doi.org/10.12928/telkomnika.v17i3.8939.

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Sheng, Lu, Jianfei Cai, Tat-Jen Cham, Vladimir Pavlovic, and King Ngi Ngan. "Visibility Constrained Generative Model for Depth-Based 3D Facial Pose Tracking." IEEE Transactions on Pattern Analysis and Machine Intelligence 41, no. 8 (2019): 1994–2007. http://dx.doi.org/10.1109/tpami.2018.2877675.

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