Presenting an Effective Algorithm for Tracking of Moving ObjectBased on Support Vector Machine
سال انتشار: 1394
نوع سند: مقاله کنفرانسی
زبان: انگلیسی
مشاهده: 663
فایل این مقاله در 10 صفحه با فرمت PDF قابل دریافت می باشد
- صدور گواهی نمایه سازی
- من نویسنده این مقاله هستم
استخراج به نرم افزارهای پژوهشی:
شناسه ملی سند علمی:
REGCMAES02_152
تاریخ نمایه سازی: 30 دی 1394
چکیده مقاله:
In this paper, an effective algorithm has been presented for object tracking in videoimages using color and texture features and with the help of accelerated support vector machine. In the proposed method, object region is firstly determined by user in the first frame; then, a region as area as the object and around it is considered as background. After that, color and texture features are extracted from object and background regions, trained to the support vector machine having been accelerated by subtracting training vectors, and tested. The first output will be a binary image in which the object has been exactly separated from its surrounding background. Then, color and texture features of the exact background region being obtained in the previous stage are developed in order to become resistant against background changes in next frames. In the following, features of object and developed background are used again for training of support vector machine and they have been used for recognition of object pixels in the next frame. In the proposed method, center of gravity of object and mean shift process have been used for object locating.
کلیدواژه ها:
نویسندگان
Hamed Mohammadi Azni
Computer and IT engineering Faculty, Islamic Azad University, Qazvin Branch, Iran
Fariborz Mahmudi
Computer and IT engineering Faculty, Islamic Azad University, Qazvin Branch, Iran
Shahrbano Akbarpoor
Islamic Azad University, Jouybar Branch, Jouybar, Iran
مراجع و منابع این مقاله:
لیست زیر مراجع و منابع استفاده شده در این مقاله را نمایش می دهد. این مراجع به صورت کاملا ماشینی و بر اساس هوش مصنوعی استخراج شده اند و لذا ممکن است دارای اشکالاتی باشند که به مرور زمان دقت استخراج این محتوا افزایش می یابد. مراجعی که مقالات مربوط به آنها در سیویلیکا نمایه شده و پیدا شده اند، به خود مقاله لینک شده اند :