This paper describes a novel object mining system for videos. An algorithm published in a previous paper by the authors is used to segment the video into shots and extract stable tracks from them. A grouping technique is introduced to combine these stable tracks into meaningful object clusters. These clusters are used in mining similar objects. Compared to other object mining systems, our approach mines more instances of similar objects in different shots. The proposed framework is applied to a full length feature film and improved results are shown.
|Translated title of the contribution||A novel video mining system|
|Title of host publication||IEEE International Conference on Image Processing, 2007 (ICIP 2007), San Antonio|
|Publisher||Institute of Electrical and Electronics Engineers (IEEE)|
|Pages||I-185 - I-188|
|Number of pages||4|
|Publication status||Published - Sep 2007|
|Event||International Conference on Image Processing - San Antonio, TX, United States|
Duration: 1 Sep 2007 → …
|Conference||International Conference on Image Processing|
|City||San Antonio, TX|
|Period||1/09/07 → …|
Bibliographical noteRose publication type: Conference contribution
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- object mining
- feature extraction
- object clustering