PROPOSAL FOR SPATIAL AND TEMPORAL COMPARISON IN THE ALGORITHMS FOR 3D RECONSTRUCTION

10.6036/9994 ◽  
2021 ◽  
Vol 96 (3) ◽  
pp. 237-237
Author(s):  
JESUS ANTONIO ALVAREZ CEDILLO ◽  
FERNANDO MARTINEZ PIÑON ◽  
TEODORO ALVAREZ SANCHEZ ◽  
JACOBO SANDOVAL GUTIERREZ ◽  
MARIO AGUILAR FERNANDEZ
Keyword(s):  
3D Reconstruction ◽  
Execution Time ◽  
Three Dimensions ◽  
Computer Reconstruction ◽  
Memory Space ◽  
3D Object ◽  
Temporal Comparison

In the computer reconstruction of objects in three dimensions (3D) there are two problems to solve. The first problem concerns reducing the memory space occupied by a 3D object. The second problem is to reduce the execution time to digitally display the reconstruction.

Efficient 3D Object Segmentation from Densely Sampled Light Fields with Applications to 3D Reconstruction

2016 ◽  
Vol 35 (3) ◽  
pp. 1-15 ◽  
Author(s):  
Kaan Yücer ◽  
Alexander Sorkine-Hornung ◽  
Oliver Wang ◽  
Olga Sorkine-Hornung
Keyword(s):  
3D Reconstruction ◽  
Object Segmentation ◽  
Light Fields ◽  
3D Object ◽  
3D Object Segmentation

scholarly journals Practical Time Optimization of DSP Program for High-frequency Applications

2021 ◽  
Vol 2095 (1) ◽  
pp. 012005
Author(s):  
Zhuyu Xun ◽  
Hongfa Ding ◽  
Zhou He
Keyword(s):  
Execution Time ◽  
High Frequency ◽  
Rapid Development ◽  
Power Conversion ◽  
High Frequency Power ◽  
Memory Space ◽  
Time Optimization ◽  
The Cost ◽  
Frequency Power

Abstract The rapid development of the high frequency power conversion techniques makes great demands on the methods that can reduce the execution time of the program effectively. This paper is aiming at reducing the execution time of the program in several aspects such as sampling, complex expressions, and so on. As one of the most widely applied methods, reducing the execution time of the program at the cost of the memory space is adopted in this paper. Furthermore, in order to confirm the feasibility and superiority of programs that are proposed in this paper, they are compared with other programs that can realize the same function in terms of the execution time.

scholarly journals An Efficient and Fast Partial Template Matching Technique – Enhancement in Normalized Cross Correlation

2019 ◽  
Vol 9 (1) ◽  
pp. 7232-7237
Keyword(s):  
Image Processing ◽  
Execution Time ◽  
Template Matching ◽  
Absolute Difference ◽  
Processing Efficiency ◽  
Memory Space ◽  
Matching Technique ◽  
Speed Up ◽  
Novel Method ◽  
Window Approach

Template matching forms the basis of many image processing algorithms and hence the computer vision algorithms. There are many existing template matching algorithms like Sum of Absolute Difference (SAD), Normalized SAD (NSAD), Correlation methods (CORR), Normalized CORR(NCORR), Sum of Squared Difference (SSD), and Normalized SSD(NSSD). In general, as image requires more memory space for storage and much time for processing. The above said methods involves much computation. In any processing, efficiency constraints include many factors, especially accuracy of the results and speed of processing. An approach to reduce the execution time is always most appreciated. As a result of this, a novel method of partial NCC (PNCC) template matching technique is proposed in this paper. A block window approach is used to reduce the number of operations and hence to speed up the processing. A comparative study between existing NCC algorithm and the proposed partial NCC, PNCC algorithm is done. It is experimented and results proves that the execution time is reduced by 8 - 47 times approximately based on the various template images for different main images in PNCC. The accuracy of the result obtained is 100%. This proposed algorithm works for various types of images. The experiment is repeated for various sizes of templates and different sizes of main image. Further improvement in the speed of execution can be achieved by implementation of the proposed algorithm using parallel processors. It may find its importance in the real time image processing

Three Dimensions (3D) Reconstruction of Liver Mass

2012 ◽  
Vol 03 (01) ◽  
pp. 65-67
Author(s):  
Somsit Tancharoen ◽  
Surachai Roongtanapirom ◽  
Chirotchana Suchato ◽  
Lergchai Varatorn ◽  
Noppadol Larbcharoensub ◽  
...  
Keyword(s):  
3D Reconstruction ◽  
Three Dimensions ◽  
Liver Mass

scholarly journals Voxel-Based 3D Object Reconstruction from Single 2D Image Using Variational Autoencoders

Mathematics ◽  
2021 ◽  
Vol 9 (18) ◽  
pp. 2288
Author(s):  
Rohan Tahir ◽  
Allah Bux Sargano ◽  
Zulfiqar Habib
Keyword(s):  
3D Reconstruction ◽  
3D Model ◽  
3D Models ◽  
Object Reconstruction ◽  
Data Set ◽  
3D Object ◽  
Practical Applications ◽  
3D Object Reconstruction ◽  
First Time ◽  
Memory Efficient

In recent years, learning-based approaches for 3D reconstruction have gained much popularity due to their encouraging results. However, unlike 2D images, 3D cannot be represented in its canonical form to make it computationally lean and memory-efficient. Moreover, the generation of a 3D model directly from a single 2D image is even more challenging due to the limited details available from the image for 3D reconstruction. Existing learning-based techniques still lack the desired resolution, efficiency, and smoothness of the 3D models required for many practical applications. In this paper, we propose voxel-based 3D object reconstruction (V3DOR) from a single 2D image for better accuracy, one using autoencoders (AE) and another using variational autoencoders (VAE). The encoder part of both models is used to learn suitable compressed latent representation from a single 2D image, and a decoder generates a corresponding 3D model. Our contribution is twofold. First, to the best of the authors’ knowledge, it is the first time that variational autoencoders (VAE) have been employed for the 3D reconstruction problem. Second, the proposed models extract a discriminative set of features and generate a smoother and high-resolution 3D model. To evaluate the efficacy of the proposed method, experiments have been conducted on a benchmark ShapeNet data set. The results confirm that the proposed method outperforms state-of-the-art methods.

Predictive Modeling of User Interaction Patterns for 3D Mesh Streaming

2012 ◽  
Vol 7 (4) ◽  
pp. 1-19 ◽  
Author(s):  
V. Vani ◽  
R. Pradeep Kumar ◽  
Mohan S.
Keyword(s):  
Predictive Model ◽  
Virtual Environment ◽  
User Interaction ◽  
Interaction Patterns ◽  
User Interactions ◽  
Memory Space ◽  
3D Mesh ◽  
3D Object ◽  
Network Bandwidth ◽  
3D Virtual Environment

The complexity in 3D virtual environment over the web is growing rapidly every day. This 3D virtual environment comprises of set of structured static and dynamic scenes and each scene has multiple 3D objects/meshes. Therefore, the granular level in any 3D virtual environments is the object. In 3D virtual environment, it is required to give user interactions for every 3D object and at any point of time, it is enough if the system streams and brings in only the visible portion of the object from server to the client by utilizing the limited network bandwidth and the limited client memory space. This streaming would reduce the time to present the rendered object to the requested clients. Further to reduce the time and effectively utilize the bandwidth and memory space, in proposed work, an attempt is made to exploit the user interactions on 3D object and built a predictive model. The experiment result shows that the built predictive model minimizes the rendering latency of the 3D mesh that is being streamed to the possible extent. Also, the results convey that the reduction in time is subjected to the type of 3D object that is taken for streaming and rendering.

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