NDLI: Building multi-model collaboration in detecting multimedia semantic concepts (invited paper)

Content Provider	IEEE Xplore Digital Library
Author	Hsin-Yu Ha Fleites, F.C. Shu-Ching Chen
Copyright Year	2013
Description	Author affiliation: Sch. of Comput. & Inf. Sci., Florida Int. Univ., Miami, FL, USA (Hsin-Yu Ha; Fleites, F.C.; Shu-Ching Chen)
Abstract	The booming multimedia technology is incurring a thriving multi-media data propagation. As multimedia data have become more essential, taking over a major potion of the content processed by many applications, it is important to leverage data mining methods to associate the low-level features extracted from multimedia data to high-level semantic concepts. In order to bridge the semantic gap, researchers have investigated the correlation among multiple modalities involved in multimedia data to effectively detect semantic concepts. It has been shown that multimodal fusion plays an important role in elevating the performance of both multimedia content-based retrieval and semantic concepts detection. In this paper, we propose a novel cluster-based ARC fusion method to thoroughly explore the correlation among multiple modalities and classification models. After combining features from multiple modalities, each classification model is built on one feature cluster, which is generated from our previous work FCC-MMF. The correlation between medoid of a feature cluster and a semantic concept is introduced to identify the capability of a classification model. It is further applied with the logistic regression method to refine ARC fusion method proposed in our previous work for semantic concept detection. Several experiments are conducted to compare the proposed method with other related works and the proposed method has outperform other works with higher Mean Average Precision (MAP).
Starting Page	205
Ending Page	212
File Size	735047
Page Count	8
File Format	PDF
ISBN	9781936968923
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-10-20
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	ICST
Subject Keyword	Correlation Feature Correlation Semantics Hidden Markov models Feature extraction Multi-model Fusion Multimedia communication Mathematical model Reliability Semantic concept detection
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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