A Web Replay Method for Highlights in Soccer Videos

2013 ◽  
Vol 321-324 ◽  
pp. 1209-1212
Author(s):  
Chong Wang ◽  
Yi Xin Ding ◽  
Zheng Yang Ding
Keyword(s):  
Web Service ◽  
Semantic Annotation ◽  
Experimental Results ◽  
Color Model ◽  
Heuristic Rules ◽  
Fine Grained ◽  
Speed Accuracy

A web replay method is proposed in this paper for highlights in soccer videos. Firstly, automatically detection and fine-grained semantic annotation are introduced for soccer highlights. Secondly, an adaptive grass color model and several heuristic rules are used to improve the performance of the method. Finally, a database for highlights is established for web service. Experimental results show that the proposed method has excellent analyzing speed, accuracy and practicability.

scholarly journals PLATFORMIZING KNOWLEDGE: MESS AND MEANING IN WEB 3.0 INFRASTRUCTURES

2020 ◽  
Author(s):  
Andrew Iliadis ◽  
Wesley Stevens ◽  
Jean-Christophe Plantin ◽  
Amelia Acker ◽  
Huw Davies ◽  
...  
Keyword(s):  
Semantic Web ◽  
Information Exchange ◽  
Semantic Annotation ◽  
Data Access ◽  
Web 3.0 ◽  
Fine Grained ◽  
The Status ◽  
Nature Of Information ◽  
Data Portability ◽  
Machine Readable

This panel focuses on the way that platforms have become key players in the representation of knowledge. Recently, there have been calls to combine infrastructure and platform-based frameworks to understand the nature of information exchange on the web through digital tools for knowledge sharing. The present panel builds and extends work on platform and infrastructure studies in what has been referred to as “knowledge as programmable object” (Plantin, et al., 2018), specifically focusing on how metadata and semantic information are shaped and exchanged in specific web contexts. As Bucher (2012; 2013) and Helmond (2015) show, data portability in the context of web platforms requires a certain level of semantic annotation. Semantic interoperability is the defining feature of so-called "Web 3.0"—traditionally referred to as the semantic web (Antoniou et al, 2012; Szeredi et al, 2014). Since its inception, the semantic web has privileged the status of metadata for providing the fine-grained levels of contextual expressivity needed for machine-readable web data, and can be found in products as diverse as Google's Knowledge Graph, online research repositories like Figshare, and other sources that engage in platformizing knowledge. The first paper in this panel examines the international Schema.org collaboration. The second paper investigates the epistemological implications when platforms organize data sharing. The third paper argues for the use of patents to inform research methodologies for understanding knowledge graphs. The fourth paper discusses private platforms’ extraction and collection of user metadata and the enclosure of data access.

scholarly journals Person Reidentification Model Based on Multiattention Modules and Multiscale Residuals

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Yongyi Li ◽  
Shiqi Wang ◽  
Shuang Dong ◽  
Xueling Lv ◽  
Changzhi Lv ◽  
...  
Keyword(s):  
Local Features ◽  
Attention Mechanism ◽  
Experimental Results ◽  
Original Network ◽  
Fine Grained ◽  
Backbone Network ◽  
Model Based ◽  
Local Branch ◽  
Feature Expression ◽  
Global And Local

At present, person reidentification based on attention mechanism has attracted many scholars’ interests. Although attention module can improve the representation ability and reidentification accuracy of Re-ID model to a certain extent, it depends on the coupling of attention module and original network. In this paper, a person reidentification model that combines multiple attentions and multiscale residuals is proposed. The model introduces combined attention fusion module and multiscale residual fusion module in the backbone network ResNet 50 to enhance the feature flow between residual blocks and better fuse multiscale features. Furthermore, a global branch and a local branch are designed and applied to enhance the channel aggregation and position perception ability of the network by utilizing the dual ensemble attention module, as along as the fine-grained feature expression is obtained by using multiproportion block and reorganization. Thus, the global and local features are enhanced. The experimental results on Market-1501 dataset and DukeMTMC-reID dataset show that the indexes of the presented model, especially Rank-1 accuracy, reach 96.20% and 89.59%, respectively, which can be considered as a progress in Re-ID.

An Improved Adaptive Threshold Skin Color Model

2014 ◽  
Vol 610 ◽  
pp. 358-361
Author(s):  
Hong Wei Di ◽  
Wei Xu
Keyword(s):  
Skin Color ◽  
Adaptive Threshold ◽  
Experimental Results ◽  
Color Model ◽  
Threshold Segmentation ◽  
Change Rate ◽  
Skin Segmentation ◽  
Strong Robustness ◽  
Skin Color Model ◽  
Optimum Threshold

To solve the problem that traditional threshold segmentation model is not very robust in skin segmentation under different skin colors and different illuminations, an improved adaptive skin color model is proposed. This model detects the change rate of the skin color pixels by modifying the certain threshold while fixing others, then selects the optimum threshold adaptively. The experimental results show that this algorithm can effectively distinguish skin color regions and background regions, and has strong robustness on light disturbance.

Application of the LDA Model to Semantic Annotation of Web-based English Educational Resources

2021 ◽  
Author(s):  
Wei Du ◽  
Haiyan Zhu ◽  
Teeraporn Saeheaw
Keyword(s):  
Topic Modeling ◽  
Basic Education ◽  
Semantic Annotation ◽  
Experimental Results ◽  
Educational Resources ◽  
Metadata Standard ◽  
Web Based ◽  
Teaching Content ◽  
Macroscopic Classification

Based on the LDA model, this paper builds a three-layer semantic model of Web English educational resources “document-topic-keyword”, models the semantic topics of resource documents, and obtains the semantic topics and keywords of document resources as the semantic labels of resources. The experimental results show that document LDA topic modeling is beneficial to the macroscopic classification of Web English educational resources. The experimental results show that LDA topic modeling of documents is useful for macroscopic cataloging of Web English educational resources, highlighting teaching priorities, difficulties, and interrelationships, while LDA modeling of teaching topics with the same teaching content expands the metadata generation method of resource description based on the basic education metadata standard and provides more information about the inherent characteristics of resources. The semantic information can be used to mine the semantic thematic features and detailed differences inherent in the resources, and the final performance analysis verifies the parallel computing advantages of the LDA model in a big data environment.

Representation and Display of Digital Images of Cultural Heritage: A Semantic Enrichment Approach

2021 ◽  
Vol 48 (3) ◽  
pp. 231-247
Author(s):  
Xu Tan ◽  
Xiaoxi Luo ◽  
Xiaoguang Wang ◽  
Hongyu Wang ◽  
Xilong Hou
Keyword(s):  
Cultural Heritage ◽  
Digital Images ◽  
Semantic Network ◽  
Semantic Representation ◽  
Semantic Annotation ◽  
Visual Display ◽  
Semantic Content ◽  
Entity Recognition ◽  
Semantic Enrichment ◽  
Fine Grained

Digital images of cultural heritage (CH) contain rich semantic information. However, today’s semantic representations of CH images fail to fully reveal the content entities and context within these vital surrogates. This paper draws on the fields of image research and digital humanities to propose a systematic methodology and a technical route for semantic enrichment of CH digital images. This new methodology systematically applies a series of procedures including: semantic annotation, entity-based enrichment, establishing internal relations, event-centric enrichment, defining hierarchy relations between properties text annotation, and finally, named entity recognition in order to ultimately provide fine-grained contextual semantic content disclosure. The feasibility and advantages of the proposed semantic enrichment methods for semantic representation are demonstrated via a visual display platform for digital images of CH built to represent the Wutai Mountain Map, a typical Dunhuang mural. This study proves that semantic enrichment offers a promising new model for exposing content at a fine-grained level, and establishing a rich semantic network centered on the content of digital images of CH.

Extending XML Types Using Updates

2010 ◽  
pp. 1-21 ◽  
Author(s):  
Béatrice Bouchou ◽  
Denio Duarte ◽  
Mírian Halfeld Ferrari ◽  
Martin A. Musicante
Keyword(s):  
Web Service ◽  
Xml Schema ◽  
Experimental Results ◽  
Element Content ◽  
Network Connection ◽  
Service Evolution ◽  
Xml Document ◽  
Communication Needs ◽  
Service Protocol ◽  
The Web

The XML Messaging Protocol, a part of the Web service protocol stack, is responsible for encoding messages in a common XML format (or type), so that they can be understood at either end of a network connection. The evolution of an XML type may be required in order to reflect new communication needs, materialized by slightly different XML messages. For instance, due to a service evolution, it might be interesting to extend a type in order to allow the reception of more information, when it is available, instead of always disregarding it. The authors’ proposal consists in a conservative XML schema evolution. The framework is as follows: administrators enter updates performed on a valid XML document in order to specify new documents expected to be valid, and the system computes new types accepting both such documents and previously valid ones. Changing the type is mainly changing regular expressions that define element content models. They present the algorithm that implements this approach, its properties and experimental results.

Selective Querying for Adapting Hierarchical Web Service Compositions

2011 ◽  
pp. 125-144
Author(s):  
John Harney ◽  
Prashant Doshi
Keyword(s):  
Web Service ◽  
Efficient Solution ◽  
Experimental Results ◽  
Novel Approach ◽  
Nested Structure

Web Service compositions (WSC) often operate in volatile environments where the parameters of the component services change during execution. To remain optimal, the WSC could adapt to these changes by querying the participating providers for their revised parameters. Previously, the value of changed information (VOC) has been utilized in simple WSCs to selectively query only those services whose revised parameters are expected to bring about significant changes in the composition. In many cases, however, in order to promote scalability, a WSC is formulated as a more complex, nested structure – a higher-level WSC may be composed of WSs and lower-level WSCs – inducing a natural hierarchy over the composition. This chapter presents a novel approach that extends the capabilities of VOC-driven querying to address the problem of adapting hierarchical WSCs. It shows how to compose and adapt hierarchical WSCs by first deriving a model of volatility for lower-level WSCs and then by descending down the levels of nesting and computing the VOC for WSCs at each level. Experimental results demonstrate that this approach provides an effective and efficient solution for complex, hierarchical WSCs.

An Adaptive Scheme to Achieve Fine Grained Video Scaling

2017 ◽  
Vol 8 (1) ◽  
pp. 43
Author(s):  
S Safinaz ◽  
A. V. Ravi Kumar
Keyword(s):  
Reconstruction Error ◽  
Experimental Results ◽  
Adaptive Scheme ◽  
Fine Grained ◽  
Proposed Model ◽  
Reconstruction Quality ◽  
Adaptive Reconstruction ◽  
Robust Adaptive ◽  
Parallel Configuration ◽  
Very High

<p>A robust Adaptive Reconstruction Error Minimization Convolution Neural Network (<strong> ARemCNN</strong>) architecture introduced to provide high reconstruction quality from low resolution using parallel configuration. Our proposed model can easily train the bulky datasets such as YUV21 and Videoset4.Our experimental results shows that our model outperforms many existing techniques in terms of PSNR, SSIM and reconstruction quality. The experimental results shows that our average PSNR result is 39.81 considering upscale-2, 35.56 for upscale-3 and 33.77 for upscale-4 for Videoset4 dataset which is very high in contrast to other existing techniques. Similarly, the experimental results shows that our average PSNR result is 38.71 considering upscale-2, 34.58 for upscale-3 and 33.047 for upscale-4 for YUV21 dataset.</p>

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