Accurate 3-D Reconstruction Under IoT Environments and Its Applications to Augmented Reality

Cao, Mingwei; Zheng, Liping; Jia, Wei; Lu, Huimin; Liu, Xiaoping

doi:10.1109/tii.2020.3016393

Cited by 20 publications

(7 citation statements)

References 29 publications

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“…A collaborative design platform that connects all of its different specialties can also use this to keep track of changes in construction volume caused by design changes and link them to its own estimates at any time. It can not only make the work more efficient but it can also make sure that there are not any mistakes in the design because of the coordination of different professions [31][32][33][34][35][36][37][38]. In the 3D model, more no geometric data like value boundaries and market data can be added.…”

Section: Simulation Outcomementioning

confidence: 99%

Construction of 3D Reconstruction System for Building Construction Scenes Based on Deep Learning and IoT

Wang

2022

Wireless Communications and Mobile Computing

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The developing intricacy and extent of building projects, as well as the way that construction schedule management is still mostly done by hand, has resulted in low efficiency in construction schedule management, resulting in cost overruns and legal disputes as a result of schedule delays in many projects. Existing 3D reconstruction algorithms frequently result in large there may be holes, distortions, or hazy regions in remade 3D models, but AI-based 3D remaking strategies regularly reestablish straightforward isolated parts and portray them as 3D boxes. Accordingly, these algorithmic systems are generally not sufficient for certifiable use. The primary objective of this paper is to apply the creation ill-disposed network strategy to 3D recreation works on the nature of the underlying 3D recreation model via preparing a generative ill-disposed network model to a joined state. As solo examples, just recently noticed 2D pictures are required, with no dependence on earlier information on the 3D hidden shape or reference insights. Test results show that this algorithmic structure outflanks present status of-the-workmanship 3D reproduction approaches on an average 3D recreation test set. On the common 3D remaking test set, exploratory outcomes uncover that this algorithmic structure beats the current cutting edge 3D reproduction techniques.

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Section: Simulation Outcomementioning

confidence: 99%

Construction of 3D Reconstruction System for Building Construction Scenes Based on Deep Learning and IoT

Wang

2022

Wireless Communications and Mobile Computing

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“…3D modelling software human modelling is the use of 3D software to build human models, such as the use of Maya and Drax to build human models. Now many industries use 3D modelling software, such as games and 3D animation [14].…”

Section: Current Status Of Researchmentioning

confidence: 99%

[Retracted] 3D Film Animation Image Acquisition and Feature Processing Based on the Latest Virtual Reconstruction Technology

Xiao

et al. 2021

Complexity

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In this paper, the latest virtual reconstruction technology is used to conduct in-depth research on 3D movie animation image acquisition and feature processing. This paper firstly proposes a time-division multiplexing method based on subpixel multiplexing technology to improve the resolution of integrated imaging reconstruction images. By studying the degradation effect of the reconstruction process of the 3D integrated imaging system, it is proposed to improve the display resolution by increasing the pixel point information of fixed display array units. According to the subpixel multiplexing, an algorithm to realize the reuse of pixel point information of 3D scene element image gets the element image array with new information; then, through the high frame rate light emitting diode (LED) large screen fast output of the element image array, the human eye temporary retention effect is used, so that this group of element image array information go through a plane display, to increase the limited display array information capacity thus improving the reconstructed image. In this way, the information capacity of the finite display array is increased and the display resolution of the reconstructed image is improved. In this paper, we first use the classification algorithm to determine the gender and expression attributes of the face in the input image and filter the corresponding 3D face data subset in the database according to the gender and expression attributes, then use the sparse representation theory to filter the prototype face like the target face in the data subset, then use the filtered prototype face samples to construct the sparse deformation model, and finally use the target faces. Finally, the target 3D face is reconstructed using the feature points of the target face for model matching. The experimental results show that the algorithm reconstructs faces with high realism and accuracy, and the algorithm can reconstruct expression faces.

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“…Although 2D ultrasound transducers are capable of dynamically reconstructing 3D images in real-time, the impedance of each transducer cell is much larger than that of a 1D line array, which makes impedance matching for 2D surface array transducers particularly difficult. In addition, to avoid mutual interference between sensor cells, each sensor cell needs to be at least half a wavelength away from each other [21], which in turn makes the size of the sensor cells limited. The principle of the equation is The flexibility and portability of handheld sensors allow clinicians to scan areas of ROI (region of interest) in specific orientations and positions, allowing the clinician to select the best view and scan plane.…”

Section: D Animation Image Reconstruction Technology Basismentioning

confidence: 99%

A Poisson Equation-Based Method for 3D Reconstruction of Animated Images

Lei

2021

Advances in Mathematical Physics

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3D reconstruction techniques for animated images and animation techniques for faces are important research in computer graphics-related fields. Traditional 3D reconstruction techniques for animated images mainly rely on expensive 3D scanning equipment and a lot of time-consuming postprocessing manually and require the scanned animated subject to remain in a fixed pose for a considerable period. In recent years, the development of large-scale computing power of computer-related hardware, especially distributed computing, has made it possible to come up with a real-time and efficient solution. In this paper, we propose a 3D reconstruction method for multivisual animated images based on Poisson’s equation theory. The calibration theory is used to calibrate the multivisual animated images, obtain the internal and external parameters of the camera calibration module, extract the feature points from the animated images of each viewpoint by using the corner point detection operator, then match and correct the extracted feature points by using the least square median method, and complete the 3D reconstruction of the multivisual animated images. The experimental results show that the proposed method can obtain the 3D reconstruction results of multivisual animation images quickly and accurately and has certain real-time and reliability.

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Accurate 3-D Reconstruction Under IoT Environments and Its Applications to Augmented Reality

Cited by 20 publications

References 29 publications

Construction of 3D Reconstruction System for Building Construction Scenes Based on Deep Learning and IoT

Construction of 3D Reconstruction System for Building Construction Scenes Based on Deep Learning and IoT

[Retracted] 3D Film Animation Image Acquisition and Feature Processing Based on the Latest Virtual Reconstruction Technology

A Poisson Equation-Based Method for 3D Reconstruction of Animated Images

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