کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
531694 869866 2006 23 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Clustering in video data: Dealing with heterogeneous semantics of features
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر چشم انداز کامپیوتر و تشخیص الگو
پیش نمایش صفحه اول مقاله
Clustering in video data: Dealing with heterogeneous semantics of features
چکیده انگلیسی

Unsupervised clustering is an important tool to analyze video data. Selection of an appropriate clustering scheme is governed by the suitability of the clusters it produces. It is difficult to formulate cluster suitability criteria for a domain where different feature attributes have different meanings. We propose a novel clustering strategy, tailored towards the specific requirements of clustering in video data. Our clustering methodology decouples clustering along different feature components. Our scheme chooses the clustering model so as to meet the requirements of clustering in video data. The clusters obtained from our scheme reasonably model the homogeneous color regions in a video scene in both space and time. The space–time clusters obtained by our clustering methodology can be subsequently grouped together to compose meaningful objects. Experimental comparison of our results with existing clustering techniques clearly show that our scheme takes care of many of the problems with traditional clustering schemes applied to the heterogeneous feature space of video.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Pattern Recognition - Volume 39, Issue 5, May 2006, Pages 789–811
نویسندگان
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