کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
4968750 | 1449750 | 2016 | 11 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
No spare parts: Sharing part detectors for image categorization
ترجمه فارسی عنوان
هیچ قطعات یدکی: آشکارسازهای بخشی به منظور دسته بندی تصویر
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کلمات کلیدی
دسته بندی تصویر، قطعات تشخیصی به اشتراک گذاری قسمت
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
چشم انداز کامپیوتر و تشخیص الگو
چکیده انگلیسی
This work aims for image categorization by learning a representation of discriminative parts. Different from most existing part-based methods, we argue that parts are naturally shared between image categories and should be modeled as such. We motivate our approach with a quantitative and qualitative analysis by backtracking where selected parts come from. Our analysis shows that in addition to the category parts defining the category, the parts coming from the background context and parts from other image categories improve categorization performance. Part selection should not be done separately for each category, but instead be shared and optimized over all categories. To incorporate part sharing between categories, we present an algorithm based on AdaBoost to optimize part sharing and selection, as well as fusion with the global image representation. With a single algorithm and without the need for task-specific optimization, we achieve results competitive to the state-of-the-art on object, scene, and action categories, further improving over deep convolutional neural networks and alternative part representations.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computer Vision and Image Understanding - Volume 152, November 2016, Pages 131-141
Journal: Computer Vision and Image Understanding - Volume 152, November 2016, Pages 131-141
نویسندگان
Pascal Mettes, Jan C. van Gemert, Cees G.M. Snoek,