کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
4968991 | 1449847 | 2017 | 49 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Fully-automated person re-identification in multi-camera surveillance system with a robust kernel descriptor and effective shadow removal method
ترجمه فارسی عنوان
دوباره شناسایی فرد کاملا خودکار در سیستم نظارت چند دوربین با یک توصیفگر قوی هسته و روش حذف موثر سایه
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
چشم انداز کامپیوتر و تشخیص الگو
چکیده انگلیسی
In this paper, a fully-automated person Re-ID (Re-identification) system is proposed for real scenarios of human tracking in non-overlapping camera network. The system includes two phases of human detection and Re-ID. The human ROIs (Regions of Interest) are extracted from human detection phase and then feature extraction is done on these ROIs in order to build human descriptor for Re-ID. Unlike other approaches which deal with manually-cropped human ROIs for person Re-ID, in this system, the person identity is determined based on the human ROIs extracted automatically by a combined method of human detection. Two main contributions are proposed on both phases of human detection and Re-ID in order to enhance the performance of person Re-ID system. First, an effective shadow removal method based on score fusion of density matching is proposed to get better human detection results. Second, a robust KDES (Kernel DEScriptor) is extracted from human ROI for person classification. Additionally, a new person Re-ID dataset is built in real surveillance scenarios from multiple cameras. The experiments on benchmark datasets and our own dataset show that the person Re-ID results using the proposed solutions outperform some of the state-of-the-art methods.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Image and Vision Computing - Volume 59, March 2017, Pages 44-62
Journal: Image and Vision Computing - Volume 59, March 2017, Pages 44-62
نویسندگان
Thi Thanh Thuy Pham, Thi-Lan Le, Hai Vu, Trung Kien Dao, Van Toi Nguyen,