Semantic retrieval of multimedia data

2004 ◽  
Author(s):  
Samira Hammiche ◽  
Salima Benbernou ◽  
Mohand-Sa�d Hacid ◽  
Athena Vakali
Keyword(s):  
Multimedia Data ◽  
Semantic Retrieval

Content-Based Multimedia Retrieval Using Feature Correlation Clustering and Fusion

2013 ◽  
Vol 4 (2) ◽  
pp. 46-64 ◽  
Author(s):  
Hsin-Yu Ha ◽  
Fausto C. Fleites ◽  
Shu-Ching Chen
Keyword(s):  
Clustering Algorithm ◽  
Multiple Correspondence Analysis ◽  
Majority Vote ◽  
Multimedia Data ◽  
Multimedia Retrieval ◽  
Semantic Retrieval ◽  
Data Set ◽  
Correlation Clustering ◽  
Feature Correlation ◽  
Fusion Framework

Nowadays, only processing visual features is not enough for multimedia semantic retrieval due to the complexity of multimedia data, which usually involve a variety of modalities, e.g. graphics, text, speech, video, etc. It becomes crucial to fully utilize the correlation between each feature and the target concept, the feature correlation within modalities, and the feature correlation across modalities. In this paper, the authors propose a Feature Correlation Clustering-based Multi-Modality Fusion Framework (FCC-MMF) for multimedia semantic retrieval. Features from different modalities are combined into one feature set with the same representation via a normalization and discretization process. Within and across modalities, multiple correspondence analysis is utilized to obtain the correlation between feature-value pairs, which are then projected onto the two principal components. K-medoids algorithm, which is a widely used partitioned clustering algorithm, is selected to minimize the Euclidean distance within the resulted clusters and produce high intra-correlated feature-value pair clusters. Majority vote is applied to subsequently decide which cluster each feature belongs to. Once the feature clusters are formed, one classifier is built and trained for each cluster. The correlation and confidence of each classifier are considered while fusing the classification scores, and mean average precision is used to evaluate the final ranked classification scores. Finally, the proposed framework is applied on NUS-wide Lite data set to demonstrate the effectiveness in multimedia semantic retrieval.

Inefficient Encoding as an Explanation for Age-Related Deficits in Recollection-Based Processing

2014 ◽  
Vol 28 (3) ◽  
pp. 148-161 ◽  
Author(s):  
David Friedman ◽  
Ray Johnson
Keyword(s):  
Older Adults ◽  
Young Adults ◽  
Cognitive Processes ◽  
Brain Activity ◽  
Memory Performance ◽  
Brain Regions ◽  
Semantic Retrieval ◽  
Age Related ◽  
The Face ◽  
Episodic Memories

A cardinal feature of aging is a decline in episodic memory (EM). Nevertheless, there is evidence that some older adults may be able to “compensate” for failures in recollection-based processing by recruiting brain regions and cognitive processes not normally recruited by the young. We review the evidence suggesting that age-related declines in EM performance and recollection-related brain activity (left-parietal EM effect; LPEM) are due to altered processing at encoding. We describe results from our laboratory on differences in encoding- and retrieval-related activity between young and older adults. We then show that, relative to the young, in older adults brain activity at encoding is reduced over a brain region believed to be crucial for successful semantic elaboration in a 400–1,400-ms interval (left inferior prefrontal cortex, LIPFC; Johnson, Nessler, & Friedman, 2013 ; Nessler, Friedman, Johnson, & Bersick, 2007 ; Nessler, Johnson, Bersick, & Friedman, 2006 ). This reduced brain activity is associated with diminished subsequent recognition-memory performance and the LPEM at retrieval. We provide evidence for this premise by demonstrating that disrupting encoding-related processes during this 400–1,400-ms interval in young adults affords causal support for the hypothesis that the reduction over LIPFC during encoding produces the hallmarks of an age-related EM deficit: normal semantic retrieval at encoding, reduced subsequent episodic recognition accuracy, free recall, and the LPEM. Finally, we show that the reduced LPEM in young adults is associated with “additional” brain activity over similar brain areas as those activated when older adults show deficient retrieval. Hence, rather than supporting the compensation hypothesis, these data are more consistent with the scaffolding hypothesis, in which the recruitment of additional cognitive processes is an adaptive response across the life span in the face of momentary increases in task demand due to poorly-encoded episodic memories.

Classification of means and methods of the Web semantic retrieval

2017 ◽  
pp. 030-050
Author(s):  
J.V. Rogushina ◽  
Keyword(s):  
Search Engines ◽  
Domain Knowledge ◽  
Information Needs ◽  
Web Search ◽  
User Interaction ◽  
Query Languages ◽  
Semantic Search ◽  
Semantic Retrieval ◽  
The Web

Problems associated with the improve ment of information retrieval for open environment are considered and the need for it’s semantization is grounded. Thecurrent state and prospects of development of semantic search engines that are focused on the Web information resources processing are analysed, the criteria for the classification of such systems are reviewed. In this analysis the significant attention is paid to the semantic search use of ontologies that contain knowledge about the subject area and the search users. The sources of ontological knowledge and methods of their processing for the improvement of the search procedures are considered. Examples of semantic search systems that use structured query languages (eg, SPARQL), lists of keywords and queries in natural language are proposed. Such criteria for the classification of semantic search engines like architecture, coupling, transparency, user context, modification requests, ontology structure, etc. are considered. Different ways of support of semantic and otology based modification of user queries that improve the completeness and accuracy of the search are analyzed. On base of analysis of the properties of existing semantic search engines in terms of these criteria, the areas for further improvement of these systems are selected: the development of metasearch systems, semantic modification of user requests, the determination of an user-acceptable transparency level of the search procedures, flexibility of domain knowledge management tools, increasing productivity and scalability. In addition, the development of means of semantic Web search needs in use of some external knowledge base which contains knowledge about the domain of user information needs, and in providing the users with the ability to independent selection of knowledge that is used in the search process. There is necessary to take into account the history of user interaction with the retrieval system and the search context for personalization of the query results and their ordering in accordance with the user information needs. All these aspects were taken into account in the design and implementation of semantic search engine "MAIPS" that is based on an ontological model of users and resources cooperation into the Web.

An Efficient Shot Boundary Detection Using Data-cube Searching Technique

2020 ◽  
Vol 13 (4) ◽  
pp. 798-807
Author(s):  
J. Kavitha ◽  
P. Arockia Jansi Rani ◽  
P. Mohamed Fathimal ◽  
Asha Paul
Keyword(s):  
Texture Features ◽  
Boundary Detection ◽  
Data Cube ◽  
Multimedia Data ◽  
Shot Boundary Detection ◽  
Gradual Transition ◽  
Detection Rates ◽  
Effective Manner ◽  
Shot Boundary ◽  
Shot Transitions

Background:: In the internet era, there is a prime need to access and manage the huge volume of multimedia data in an effective manner. Shot is a sequence of frames captured by a single camera in an uninterrupted space and time. Shot detection is suitable for various applications such that video browsing, video indexing, content based video retrieval and video summarization. Objective:: To detect the shot transitions in the video within a short duration. It compares the visual features of frames like correlation, histogram and texture features only in the candidate region frames instead of comparing the full frames in the video file. Methods: This paper analyses candidate frames by searching the values of frame features which matches with the abrupt detector followed by the correct cut transition frame with in the datacube recursively until it detects the correct transition frame. If they are matched with the gradual detector, then it will give the gradual transition ranges, otherwise the algorithm will compare the frames within the next datacube to detect shot transition. Results:: The total average detection rates of all transitions computed in the proposed Data-cube Search Based Shot Boundary Detection technique are 92.06 for precision, 96.92 for recall and 93.94 for f1 measure and the maximum accurate detection rate. Conclusion:: Proposed method for shot transitions uses correlation value for searching procedure with less computation time than the existing methods which compares every single frame and uses multi features such as color, edge, motion and texture features in wavelet domain.

scholarly journals Adaptive Real-Time Routing Protocol for (m,k)-Firm in Industrial Wireless Multimedia Sensor Networks

Sensors ◽  
2020 ◽  
Vol 20 (6) ◽  
pp. 1633 ◽  
Author(s):  
Beom-Su Kim ◽  
Sangdae Kim ◽  
Kyong Hoon Kim ◽  
Tae-Eung Sung ◽  
Babar Shah ◽  
...  
Keyword(s):  
Real Time ◽  
Routing Protocol ◽  
Traffic Management ◽  
Research Area ◽  
Multimedia Data ◽  
Wireless Multimedia ◽  
Multimedia Sensor Networks ◽  
Proposed Model ◽  
Event Information ◽  
Firm Model

Many applications are able to obtain enriched information by employing a wireless multimedia sensor network (WMSN) in industrial environments, which consists of nodes that are capable of processing multimedia data. However, as many aspects of WMSNs still need to be refined, this remains a potential research area. An efficient application needs the ability to capture and store the latest information about an object or event, which requires real-time multimedia data to be delivered to the sink timely. Motivated to achieve this goal, we developed a new adaptive QoS routing protocol based on the (m,k)-firm model. The proposed model processes captured information by employing a multimedia stream in the (m,k)-firm format. In addition, the model includes a new adaptive real-time protocol and traffic handling scheme to transmit event information by selecting the next hop according to the flow status as well as the requirement of the (m,k)-firm model. Different from the previous approach, two level adjustment in routing protocol and traffic management are able to increase the number of successful packets within the deadline as well as path setup schemes along the previous route is able to reduce the packet loss until a new path is established. Our simulation results demonstrate that the proposed schemes are able to improve the stream dynamic success ratio and network lifetime compared to previous work by meeting the requirement of the (m,k)-firm model regardless of the amount of traffic.

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