Video concept detection using Hadoop MapReduce framework
Indexing video collection with a large set of video concepts allows us to employ a query-by-concept paradigm. Through concept detection, the task is to detect in the shot- segmented video data the presence of a set of pre-defined semantic concepts. Columbia University provided 374 detectors based on...
| Main Authors: | , , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2014
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| Online Access: | http://psasir.upm.edu.my/id/eprint/38455/1/38455.pdf |
| _version_ | 1825949229567180800 |
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| author | Affendey, Lilly Suriani Chamasemani, Fereshteh Falah Ishak, Iskandar Sidi, Fatimah |
| author_facet | Affendey, Lilly Suriani Chamasemani, Fereshteh Falah Ishak, Iskandar Sidi, Fatimah |
| author_sort | Affendey, Lilly Suriani |
| collection | UPM |
| description | Indexing video collection with a large set of video concepts allows us to employ a query-by-concept paradigm. Through concept detection, the task is to detect in the shot- segmented video data the presence of a set of pre-defined semantic concepts. Columbia University provided 374 detectors based on color, texture and edge features, and their unsupervised classifier fusion that can be utilized for concepts training purposes. We had successfully implemented a Concept-based Video retrieval System (CBVRS) to support query-by-concept. However, one of the main challenges is to reduce the training time of concepts to support the video concept detection. This paper presents an alternative architecture to overcome the issue. The proposed CBVRS framework, which consists of three main modules i.e. pre-processing, video analysis, and annotation module, shall utilize the Hadoop MapReduce framework for fast computation of the concept detection. |
| first_indexed | 2024-03-06T08:41:21Z |
| format | Conference or Workshop Item |
| id | upm.eprints-38455 |
| institution | Universiti Putra Malaysia |
| language | English |
| last_indexed | 2024-03-06T08:41:21Z |
| publishDate | 2014 |
| record_format | dspace |
| spelling | upm.eprints-384552016-07-29T07:50:56Z http://psasir.upm.edu.my/id/eprint/38455/ Video concept detection using Hadoop MapReduce framework Affendey, Lilly Suriani Chamasemani, Fereshteh Falah Ishak, Iskandar Sidi, Fatimah Indexing video collection with a large set of video concepts allows us to employ a query-by-concept paradigm. Through concept detection, the task is to detect in the shot- segmented video data the presence of a set of pre-defined semantic concepts. Columbia University provided 374 detectors based on color, texture and edge features, and their unsupervised classifier fusion that can be utilized for concepts training purposes. We had successfully implemented a Concept-based Video retrieval System (CBVRS) to support query-by-concept. However, one of the main challenges is to reduce the training time of concepts to support the video concept detection. This paper presents an alternative architecture to overcome the issue. The proposed CBVRS framework, which consists of three main modules i.e. pre-processing, video analysis, and annotation module, shall utilize the Hadoop MapReduce framework for fast computation of the concept detection. 2014 Conference or Workshop Item NonPeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/38455/1/38455.pdf Affendey, Lilly Suriani and Chamasemani, Fereshteh Falah and Ishak, Iskandar and Sidi, Fatimah (2014) Video concept detection using Hadoop MapReduce framework. In: Malaysian National Conference of Databases 2014 (MaNCoD 2014), 17 Sept. 2014, Universiti Putra Malaysia, Serdang, Selangor. (pp. 46-49). (Unpublished) http://mancod2014.blogspot.my/p/proceedings.html |
| spellingShingle | Affendey, Lilly Suriani Chamasemani, Fereshteh Falah Ishak, Iskandar Sidi, Fatimah Video concept detection using Hadoop MapReduce framework |
| title | Video concept detection using Hadoop MapReduce framework |
| title_full | Video concept detection using Hadoop MapReduce framework |
| title_fullStr | Video concept detection using Hadoop MapReduce framework |
| title_full_unstemmed | Video concept detection using Hadoop MapReduce framework |
| title_short | Video concept detection using Hadoop MapReduce framework |
| title_sort | video concept detection using hadoop mapreduce framework |
| url | http://psasir.upm.edu.my/id/eprint/38455/1/38455.pdf |
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