Structured High-Level Indexing of Visual Data Content

1999 ◽  
pp. 409-416 ◽  
Author(s):  
Audrey M. Tam ◽  
Clement H. C. Leung
Keyword(s):  
Visual Data ◽  
Data Content ◽  
High Level

scholarly journals Protection of Visual Data Transmission for Vessel Traffic Systems Using Joint Fingerprinting and Decryption Method Based on Modified Hill Cipher

2012 ◽  
Vol 19 (2) ◽  
pp. 5-17
Author(s):  
Bartosz Czaplewski ◽  
Krzysztof Czaplewski
Keyword(s):  
Data Transmission ◽  
Video On Demand ◽  
Multimedia Data ◽  
Visual Data ◽  
Collusion Attack ◽  
Collusion Attacks ◽  
Traffic Systems ◽  
Industrial Cameras ◽  
High Level ◽  
Fingerprinting Methods

Abstract Vessel traffic systems provide a high level of safety on coastal waters due to coastal radar stations and industrial cameras transmitting information to traffic supervision centers, as well. To improve a vessel traffic services is very important to ensure the speed and secrecy for the transmission of video images. The paper presents the basic issues of the multimedia data protection by digital watermarking and fingerprinting methods. Main applications for such digital marking were described in the paper as well as its requirements. Furthermore, the importance of multicast transmission for fingerprinting methods was presented by comparing the scalability of methods using only unicast transmissions and methods using multicast transmissions. The paper also presents the greatest threat to fingerprinting methods, which are attacks performed by more than one pirate. These attacks are called collusion attacks. The criteria that should be followed during identifying rogue users taking part in the collusion attack on the security systems has been presented. The paper also contains description of the extended Hillcast method, which belongs to the group of JFD (Joint Fingerprinting and Decryption) methods. The method provides a cryptographic security and digital fingerprinting of multimedia content, while maintaining high scalability. Main purpose of this method is VoD (Video on Demand) service, but it can also be used in vessel traffic supervision systems, such as VTS and AIS. In the last part of paper, there are results of studies which indicate high resistance to most common collusion attacks. Method proposed by authors can enhance the security of visual data transmission in vessel traffic systems.

Pola Deformasi (Deformation Pattern) Mineralisasi Emas Sulfida Rendah di Zona Neo-Tektonik Selat Sunda

PROMINE ◽  
2018 ◽  
Vol 6 (1) ◽  
pp. 12-18
Author(s):  
Dudi Nasrudin Usman ◽  
Nana Sulaksana ◽  
Febri Hirnawan ◽  
Iyan Haryanto
Keyword(s):  
Data Processing ◽  
Tectonic Activity ◽  
Deformation Pattern ◽  
Gold Content ◽  
Eurasian Plate ◽  
Average Value ◽  
Data Content ◽  
The Difference ◽  
Two Parameters ◽  
High Level

The Sunda Strait is one of the zones of the Eurasian plate encounters with fairly active Indian plates. This can be seen based on volcanic activity that occurred in the region of Mount Krakatau. But there are unique things that are important to learn is tectonic movement with geological forces that work to produce cracks in rocks, the formation of volcanoes and cracks that occur produce mineralized zones, especially in the Formation of Honje and Formation Cipacar and more widely known as Bayah Dome. The presence of mineralization of the Honje Formation and Cipacar Formation is particularly located in the District of Cimanggu, Mangku Alam Village, the existence of gold mining activities proves that the mineralization of the region has the potential of economy. The presence of mineralization will not be separated from the presence of rock fractures in the two formations that have different geological age of the Late Miocene and Plistocene. Both formations are hindered by the presence of unconformity fields. This study aims to prove the extent of tectonic activity occurring in the Honje Formation with the final Miocene age forwarded to the Cipacar Formation even though obstructed by the field of nonconformity with the results of field data processing based on the value of RMR and RQD value. Both parameters are also studied to determine the extent to which the RQD value determines the magnitude of the grade value of Gold (Au). The distribution of RMR value and rock RQD value is taken from 2 different rock units, ie, andesite rock units in Honje Formation and tuff rock units in Cipacar Formation, based on the data distribution around 125 RMR observation points and 117 RQD observation points in the field are processed by using method test the average difference of the two parameters from 2 different rock units. In addition, the RQD value was correlated to the high level of gold content using correlation regression test of 78 data content and RQD value. Results of processing and discussion of data indicate that between the value of RMR in andesit unit and tuff unit there is no difference in value means H0 accepted by tcount = 0.556 <ttable = 1.995, as well as the difference test average RQD value where the results show that there is no difference between the average value of RQD andesite rock units in Honje Formation and tuff rock units in Cipacar Formation with tcount = 1.714 <ttable = 1.995, based on the results of data processing it can be explained that the tectonic activity in Honje Formation with the final Miocene age is forwarded to Cipacar Formation even if obstructed the field of dissonance means that tectonic activity of the region is inferred as neotectonic activity of West Java. In addition, one more thing that can be concluded that the relationship of RQD with Gold content (Au) based on statistical test the greater the value of RQD then the value of gold content (Au) the greater the test results regression correlation value PValue (Significance) = 0.013 with the equation y = -0.715x + 75.882 value R2 42.39%. Because Significance value> 0.05 then H0 DENIED, so H1 accepted, where the higher the value of the Big Au content then the RQD Value the greater.

scholarly journals High-Level Toolset For Comprehensive Visual Data Analysis and Model Validation

2017 ◽  
Vol 108 ◽  
pp. 2090-2099 ◽  
Author(s):  
Konstantin Ryabinin ◽  
Svetlana Chuprina
Keyword(s):  
Data Analysis ◽  
Model Validation ◽  
Visual Data ◽  
High Level

scholarly journals Joint compression and encryption of visual data using orthogonal parametric transforms

2016 ◽  
Vol 64 (2) ◽  
pp. 373-382 ◽  
Author(s):  
D. Puchala ◽  
M. M. Yatsymirskyy
Keyword(s):  
Experimental Studies ◽  
Data Encryption ◽  
Visual Data ◽  
Compression Performance ◽  
First Order ◽  
Block Quantization ◽  
Encryption Schemes ◽  
Novel Method ◽  
High Level ◽  
High Computational Efficiency

Abstract In this paper, we introduce a novel method of joint compression and encryption of visual data. In the proposed approach the compression stage is based on block quantization while the encryption uses fast parametric orthogonal transforms of arbitrary forms in combination with a novel scheme of intra-block mixing of data vectors. Theoretical analysis of the method indicates no impact of encryption stage on the effectiveness of block quantization with an additional step of first order entropy coding. Moreover, a series of experimental studies involving natural images and JPEG lossy compression standard were performed. Here, the obtained results indicate a high level of visual content concealment with only a small reduction of compression performance. An additional analysis of security allows to state that the proposed method is resistant to cryptanalytic attacks known for visual data encryption schemes including the most efficient NZCA attack. The proposed method can be also characterized by high computational efficiency and feasibility of hardware realizations.

Research on Uncertainty of Video Content Retrieval Based on Semantic

2011 ◽  
Vol 204-210 ◽  
pp. 814-817
Author(s):  
Jie Xin Zhang
Keyword(s):  
Cloud Model ◽  
Color Space ◽  
Global Scale ◽  
Video Data ◽  
Video Content ◽  
Uncertainty Reasoning ◽  
Content Retrieval ◽  
Semantic Concepts ◽  
Data Content ◽  
High Level

Nowadays, video media data is already facilitates generation, transmission, storage and circulation on the global scale. Video data is geometrically fast as the rate of growth, the video data processing and analysis have lagged behind the pace of development in the growth of data, resulting in large amounts of data is wasted. Therefore, it becomes an urgent need for efficient retrieval of video data content. In this paper, firstly, starting from the color feature, the color space of digital mapping and semantic color space conversion technology is proposed according to the problem of Semantic concepts for video does not match with the perceived characteristics. And then we realize the mapping from the low-level features to high-level semantic. Finally, semantic rules of uncertainty reasoning based on cloud model established to complete video content retrieval.

scholarly journals Research Infrastructure Contact Zones: A method to visualise and align the activities of major biodiversity informatics initiatives

2021 ◽  
Vol 5 ◽  
Author(s):  
Vincent Smith ◽  
Aino Juslén ◽  
Ana Casino ◽  
Francois Dusoulier ◽  
Lisa French ◽  
...  
Keyword(s):  
Molecular Data ◽  
Research Infrastructure ◽  
Global Alignment ◽  
Biodiversity Informatics ◽  
Data Standards ◽  
Global Biodiversity Information Facility ◽  
Ecosystem Research ◽  
Data Content ◽  
High Level

In an effort to characterise the various dimensions of activity within the biodiversity informatics landscape, we developed a framework to survey these dimensions for ten major organisations*1 relative to both their current activities and long-term strategic ambitions. This survey assessed the contact between these infrastructure organisations by capturing the breadth of activities for each infrastructure across five categories (data, standards, software, hardware and policy), for nine types of data (specimens, collection descriptions, opportunistic observations, systematic observations, taxonomies, traits, geological data, molecular data, and literature), and for seven phases of activity (creation, aggregation, access, annotation, interlinkage, analysis, and synthesis). This generated a dataset of 6,300 verified observations, which have been scored and validated by leading members of each infrastructure organisation. In this analysis of the resulting data, we address a set of high-level questions about the overall biodiversity informatics landscape, looking at the greatest gaps, overlap and possible rate-limiting steps. Across the infrastructure organisations, we also explore how far each is in relation to achieving its ambitions and the extent of its niche relative to other organisations. Our results show that when viewed by scope, most infrastructures occupy a relatively narrow niche in the overall landscape of activity, with the notable exception of the Global Biodiversity Information Facility (GBIF) and possibly LifeWatch. Niches associated with molecular data and biological taxonomy are very well filled, suggesting there is still considerable room for growth in other areas, with the Distributed System of Scientific Collections (DiSSCo) and the Integrated European Long-Term Ecosystem Research Infrastructure (eLTER RI) showing the highest levels of difference between their current activities and stated ambitions, potentially reflecting the relative youth of these organisations. iNaturalist, the Biodiversity Heritage Library and Catalogue of Life all occupy narrow and tightly circumscribed niches. These organisations are also amongst the closest to achieving their stated ambitions within their respective areas of activity. The largest gaps in infrastructure activity relate to the development of hardware and standards, with many gaps set to be addressed if the stated ambitions of those surveyed come to fruition. Nevertheless, some gaps persist, outlining a potential role for this survey as a planning tool to help coordinate and align investment in future biodiversity informatics activities. GBIF and LifeWatch are the two infrastructures where there is the most similarity in ambition with DiSSCo, with the greatest overlap concentrated on activities related to data/content, specimen data and their shared ambition to interlink information. While overlap appears intense, the analysis is limited by the resolution of the survey framework and ignores existing collaborations between infrastructures. In addition to presenting the results of this survey, we outline our plans to publish this work and a proposal to develop the methodology as an interactive web-based tool. This would allow other projects and infrastructures to self-score their activities and visualise their niche within the current landscape, encouraging better global alignment of activities. For example, our results should make it easier for initiatives to strengthen collaboration and differentiate work when their activities overlap. Likewise, this approach would be useful for funding agencies when targeting gaps in the informatics landscape or increasing the technical maturity of certain critical activities, e.g., to improve immature data standards. While no framework is perfect, we hope to encourage a dialogue on the potential for taking an algorithmic approach to community alignment and see this as a means of strengthening community cooperation when addressing problems that require global cooperation.

scholarly journals Deep neural network-based fusion model for emotion recognition using visual data

2021 ◽  
Author(s):  
Luu-Ngoc Do ◽  
Hyung-Jeong Yang ◽  
Hai-Duong Nguyen ◽  
Soo-Hyung Kim ◽  
Guee-Sang Lee ◽  
...  
Keyword(s):  
Emotion Recognition ◽  
Video Data ◽  
Visual Data ◽  
Fusion Model ◽  
Video Information ◽  
Selection Step ◽  
The Face ◽  
Sequential Information ◽  
Public Datasets ◽  
High Level

AbstractIn this study, we present a fusion model for emotion recognition based on visual data. The proposed model uses video information as its input and generates emotion labels for each video sample. Based on the video data, we first choose the most significant face regions with the use of a face detection and selection step. Subsequently, we employ three CNN-based architectures to extract the high-level features of the face image sequence. Furthermore, we adjusted one additional module for each CNN-based architecture to capture the sequential information of the entire video dataset. The combination of the three CNN-based models in a late-fusion-based approach yields a competitive result when compared to the baseline approach while using two public datasets: AFEW 2016 and SAVEE.

Bridging the Semantic Gap in Image Retrieval

2002 ◽  
pp. 14-36 ◽  
Author(s):  
Rhong Zhao ◽  
William I. Grosky
Keyword(s):  
Information Retrieval ◽  
Image Retrieval ◽  
Research Field ◽  
Visual Features ◽  
Semantic Features ◽  
Visual Data ◽  
Image Content ◽  
Low Level ◽  
Significant Research ◽  
High Level

The emergence of multimedia technology and the rapidly expanding image and video collections on the Internet have attracted significant research efforts in providing tools for effective retrieval and management of visual data. Image retrieval is based on the availability of a representation scheme of image content. Image content descriptors may be visual features such as color, texture, shape, and spatial relationships, or semantic primitives. Conventional information retrieval was based solely on text, and those approaches to textual information retrieval have been transplanted into image retrieval in a variety of ways. However, “a picture is worth a thousand words.” Image content is much more versatile compared with text, and the amount of visual data is already enormous and still expanding very rapidly. Hoping to cope with these special characteristics of visual data, content-based image retrieval methods have been introduced. It has been widely recognized that the family of image retrieval techniques should become an integration of both low-level visual features addressing the more detailed perceptual aspects and high-level semantic features underlying the more general conceptual aspects of visual data. Neither of these two types of features is sufficient to retrieve or manage visual data in an effective or efficient way (Smeulders, et al., 2000). Although efforts have been devoted to combining these two aspects of visual data, the gap between them is still a huge barrier in front of researchers. Intuitive and heuristic approaches do not provide us with satisfactory performance. Therefore, there is an urgent need of finding the latent correlation between low-level features and high-level concepts and merging them from a different perspective. How to find this new perspective and bridge the gap between visual features and semantic features has been a major challenge in this research field. Our chapter addresses these issues.

Interactive Visual Data Mining

2008 ◽  
pp. 1638-1642
Author(s):  
Shouhong Wang ◽  
Hai Wang
Keyword(s):  
Data Mining ◽  
Knowledge Discovery ◽  
Visual Data ◽  
Visual Data Mining ◽  
Data Mining Techniques ◽  
General Proposition ◽  
Level Information ◽  
High Level ◽  
Interactive Visual Data Mining ◽  
Structure Of Knowledge

In the data mining field, people have no doubt that high level information (or knowledge) can be extracted from the database through the use of algorithms. However, a one-shot knowledge deduction is based on the assumption that the model developer knows the structure of knowledge to be deducted. This assumption may not be invalid in general. Hence, a general proposition for data mining is that, without human-computer interaction, any knowledge discovery algorithm (or program) will fail to meet the needs from a data miner who has a novel goal (Wang, S. & Wang, H., 2002). Recently, interactive visual data mining techniques have opened new avenues in the data mining field (Chen, Zhu, & Chen, 2001; de Oliveira & Levkowitz, 2003; Han, Hu & Cercone, 2003; Shneiderman, 2002; Yang, 2003).

Interactive Visual Data Mining

2011 ◽  
pp. 644-646
Author(s):  
Shouhong Wang ◽  
Hai Wang
Keyword(s):  
Data Mining ◽  
Knowledge Discovery ◽  
Visual Data ◽  
Visual Data Mining ◽  
Data Mining Techniques ◽  
General Proposition ◽  
Level Information ◽  
High Level ◽  
Interactive Visual Data Mining ◽  
Structure Of Knowledge

In the data mining field, people have no doubt that high level information (or knowledge) can be extracted from the database through the use of algorithms. However, a one-shot knowledge deduction is based on the assumption that the model developer knows the structure of knowledge to be deducted. This assumption may not be invalid in general. Hence, a general proposition for data mining is that, without human-computer interaction, any knowledge discovery algorithm (or program) will fail to meet the needs from a data miner who has a novel goal (Wang, S. & Wang, H., 2002). Recently, interactive visual data mining techniques have opened new avenues in the data mining field (Chen, Zhu, & Chen, 2001; de Oliveira & Levkowitz, 2003; Han, Hu & Cercone, 2003; Shneiderman, 2002; Yang, 2003).

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