کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
6854300 1437411 2018 9 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Deep convolutional framework for abnormal behavior detection in a smart surveillance system
ترجمه فارسی عنوان
چارچوب عمودی کانولوشن برای تشخیص رفتار غیر طبیعی در سیستم نظارت هوشمند
کلمات کلیدی
00-01، 99-00، شناخت رفتار، شبکه عصبی متقاطع، حافظه طولانی مدت، سیستم نظارت هوشمند
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
چکیده انگلیسی
The ability to instantly detect risky behavior in video surveillance systems is a critical issue in a smart surveillance system. In this paper, a unified framework based on a deep convolutional framework is proposed to detect abnormal human behavior from a standard RGB image. The objective of the unified structure is to improve detection speed while maintaining recognition accuracy. The deep convolutional framework consists of (1) a human subject detection and discrimination module that is proposed to solve the problem of separating object entities, in contrast to previous object detection algorithms, (2) a posture classification module to extract spatial features of abnormal behavior, and (3) an abnormal behavior detection module based on long short-term memory (LSTM). Experiments on a benchmark dataset evaluate the potential of the proposed method in the context of smart surveillance. The results indicate that the proposed method provides satisfactory performance in detecting abnormal behavior in a real-world scenario.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Engineering Applications of Artificial Intelligence - Volume 67, January 2018, Pages 226-234
نویسندگان
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