scholarly journals Region-Based Static Video Stitching for Reduction of Parallax Distortion

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 4020
Author(s):  
Keon-woo Park ◽  
Yoo-Jeong Shim ◽  
Myeong-jin Lee
Keyword(s):  
Semantic Segmentation ◽  
Geometric Distortion ◽  
Video Sequences ◽  
Video Frame ◽  
Feature Points ◽  
Semantic Class ◽  
Video Stitching ◽  
Consistent Feature ◽  
Conventional Methods

In this paper, we propose a semantic segmentation-based static video stitching method to reduce parallax and misalignment distortion for sports stadium scenes with dynamic foreground objects. First, video frame pairs for stitching are divided into segments of different classes through semantic segmentation. Region-based stitching is performed on matched segment pairs, assuming that segments of the same semantic class are on the same plane. Second, to prevent degradation of the stitching quality of plain or noisy videos, the homography for each matched segment pair is estimated using the temporally consistent feature points. Finally, the stitched video frame is synthesized by stacking the stitched matched segment pairs and the foreground segments to the reference frame plane by descending order of the area. The performance of the proposed method is evaluated by comparing the subjective quality, geometric distortion, and pixel distortion of video sequences stitched using the proposed and conventional methods. The proposed method is shown to reduce parallax and misalignment distortion in segments with plain texture or large parallax, and significantly improve geometric distortion and pixel distortion compared to conventional methods.

scholarly journals Adaptive Reservation of Network Resources According to Video Classification Scenes

Sensors ◽  
2021 ◽  
Vol 21 (6) ◽  
pp. 1949
Author(s):  
Lukas Sevcik ◽  
Miroslav Voznak
Keyword(s):  
User Satisfaction ◽  
Quality Evaluation ◽  
Spatial Information ◽  
Service Providers ◽  
Video Quality ◽  
Subjective Assessment ◽  
Video Sequences ◽  
Network Resources ◽  
Proposed Model

Video quality evaluation needs a combined approach that includes subjective and objective metrics, testing, and monitoring of the network. This paper deals with the novel approach of mapping quality of service (QoS) to quality of experience (QoE) using QoE metrics to determine user satisfaction limits, and applying QoS tools to provide the minimum QoE expected by users. Our aim was to connect objective estimations of video quality with the subjective estimations. A comprehensive tool for the estimation of the subjective evaluation is proposed. This new idea is based on the evaluation and marking of video sequences using the sentinel flag derived from spatial information (SI) and temporal information (TI) in individual video frames. The authors of this paper created a video database for quality evaluation, and derived SI and TI from each video sequence for classifying the scenes. Video scenes from the database were evaluated by objective and subjective assessment. Based on the results, a new model for prediction of subjective quality is defined and presented in this paper. This quality is predicted using an artificial neural network based on the objective evaluation and the type of video sequences defined by qualitative parameters such as resolution, compression standard, and bitstream. Furthermore, the authors created an optimum mapping function to define the threshold for the variable bitrate setting based on the flag in the video, determining the type of scene in the proposed model. This function allows one to allocate a bitrate dynamically for a particular segment of the scene and maintains the desired quality. Our proposed model can help video service providers with the increasing the comfort of the end users. The variable bitstream ensures consistent video quality and customer satisfaction, while network resources are used effectively. The proposed model can also predict the appropriate bitrate based on the required quality of video sequences, defined using either objective or subjective assessment.

Elimination of Unnecessary Feature Points by Semantic Segmentation Aimed at Improving the Accuracy of Feature-Based SLAM

2021 ◽  
Vol 2021 (0) ◽  
pp. 1P2-C06
Author(s):  
Tomoki HAKOTANI ◽  
Ryota SAKUMA ◽  
Masanao KOEDA ◽  
Akihiro HAMADA ◽  
Atsuro SAWADA ◽  
...  
Keyword(s):  
Semantic Segmentation ◽  
Feature Points ◽  
Feature Based

Data normalization for training and analysis of the MaskRCNN model using the k-means method for computer vision of smart refrigerator

2021 ◽  
Vol 4 ◽  
pp. 74-80
Author(s):  
M. G. Dorrer ◽  
◽  
A.E. Alekhina ◽  
Keyword(s):  
Computer Vision ◽  
Semantic Segmentation ◽  
Correct Choice ◽  
Training Sample ◽  
Artificial Vision ◽  
K Value ◽  
High K ◽  
Real World Datasets ◽  
Segmentation Problem

This paper proposes using the k-means method for the controlled adjustment of the training sample for semantic image segmentation in the artificial vision of a smart refrigerator. To solve this problem, a new two-stage architecture for computer vision is proposed. In the proposed architecture, various sets of settings for optimizing the contrast of images are used to classify pixels according to their belonging to fragments of the studied image. Extensive experimental evaluation shows that the proposed method has critical advantages over existing work. Firstly, the obtained pixel classes can be directly clustered into semantic groups using k-means. Secondly, the method can be used for additional training of artificial intelligence in solving the semantic segmentation problem. The developers propose an approach to the correct choice of the number k of centroids to obtain good quality clusters, which is difficult to determine at a high k value. To overcome the problem of initializing the k-means method, an incremental k-means clustering method is proposed, which improves the quality of clusters to reduce the sum of squared errors. Comprehensive experiments have been carried out compared to the traditional k-means algorithm and its new versions to evaluate the performance of the proposed method on synthetically generated datasets and some real-world datasets.

scholarly journals Content Visualization: An Evaluation of PowerPoint Effectiveness as a Learning Tool for Students

2018 ◽  
Vol 7 (2.29) ◽  
pp. 840
Author(s):  
Devi Pratami ◽  
Asti Amalia Nur Fajrillah ◽  
Tien Fabrianti Kusumasari
Keyword(s):  
Conventional Method ◽  
Test Score ◽  
Visual Presentation ◽  
Statistical Test ◽  
Learning Tool ◽  
The World ◽  
Slide Show ◽  
Conventional Methods ◽  
Education Field

PowerPoint is a slide show presentation program from Microsoft, which also one of the most widely used programs to develop visual presentation all over the world. PowerPoint has become enormously popular because of the functionalities offered and since it is designed to be easy to use. Previous researchers stated PowerPoint as one of the best tool to facilitate users to deliver idea/objective/goal, especially in education field. But some of the researchers argue that in today’s environment, PowerPoint no longer be the best tool to deliver information. This research aims to evaluate and design the content of the slide which influences the level of students understanding on information being presented. This research will be comparing three methods at once, which are a conventional method where the material course will be presented without any PowerPoint and are limited to boards and books. The second method will be a material-course presentation using a PowerPoint where it was using an aesthetically pleasing and methodically correct PowerPoint. And the last method would be the combination between the two. By using a statistical test ANOVA that among three methods there is no significance impact to the students understanding. Nevertheless, based on the test score that are done after treatment the results show that the quality of PowerPoint slide has an influence to the level of students understanding compared to conventional methods (blackboard and textbook). But only attractive slide itself is insufficient to improve students understanding, this study will incorporate conventional method and attractive slide through content visualization in order to gives a better impact on students understanding.  

scholarly journals Object detection and tracking in video sequences: formalization, metrics and results

Informatics ◽  
2021 ◽  
Vol 18 (1) ◽  
pp. 43-60
Author(s):  
R. P. Bohush ◽  
S. V. Ablameyko
Keyword(s):  
Moving Objects ◽  
Human Movement ◽  
Video Sequences ◽  
Multiple Objects ◽  
Movement Trajectories ◽  
Detection And Tracking ◽  
Form Features ◽  
One And Many ◽  
Tracking Objects

One of the promising areas of development and implementation of artificial intelligence is the automatic detection and tracking of moving objects in video sequence. The paper presents a formalization of the detection and tracking of one and many objects in video. The following metrics are considered: the quality of detection of tracked objects, the accuracy of determining the location of the object in a frame, the trajectory of movement, the accuracy of tracking multiple objects. Based on the considered generalization, an algorithm for tracking people has been developed that uses the tracking through detection method and convolutional neural networks to detect people and form features. Neural network features are included in a composite descriptor that also contains geometric and color features to describe each detected person in the frame. The results of experiments based on the considered criteria are presented, and it is experimentally confirmed that the improvement of the detector operation makes it possible to increase the accuracy of tracking objects. Examples of frames of processed video sequences with visualization of human movement trajectories are presented.

Use of the complex baking improver «Unipan Total» in the technology of bakery products

2021 ◽  
Vol 30 (6) ◽  
pp. 50-55
Author(s):  
S.V. Borisova ◽  
◽  
N.U. Mukhametchina ◽  
G.S. Sagdeeva ◽  
◽  
...  
Keyword(s):  
Quality Indicators ◽  
Weight Control ◽  
Wheat Bread ◽  
Bakery Products ◽  
High Quality ◽  
Quality Product ◽  
Conventional Methods ◽  
High Quality Product

The results of the study of the influence of various concentrations of the complex bakery improver «Unipan Total» on the properties of semi-finished products and quality indicators of bakery products are presented. Bakery products were produced using the unpaired method according to a unified recipe for Dniprovskaya buns. To obtain a high-quality product, prototypes were prepared from wheat bakery flour of the highest grade with the addition of the «Unipan Total» improver at a concentration of 0,5 to 8% to the flour weight, control ones without the improver. Organoleptic and physicochemical indicators of the quality of wheat bread samples were determined by conventional methods.

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