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رهگیری بصری طولانی مدت اهداف دلخواه بر اساس راهگزین بین دو روش رهگیری سنتی و فن یادگیری ژرف | ||
مجله مهندسی برق دانشگاه تبریز | ||
دوره 54، شماره 4 - شماره پیاپی 110، آذر 1403، صفحه 391-402 اصل مقاله (1.08 M) | ||
نوع مقاله: علمی-پژوهشی | ||
شناسه دیجیتال (DOI): 10.22034/tjee.2024.59362.4766 | ||
نویسندگان | ||
محمدامین باقرزاده1؛ میرهادی سیدعربی* 2؛ سید ناصر رضوی3 | ||
1دانشجوی دکتری، دانشکده مهندسی برق و کامپیوتر، دانشگاه تبریز، تبریز، ایران | ||
2استاد، دانشکده مهندسی برق و کامپیوتر، دانشگاه تبریز، تبریز، ایران | ||
3استادیار، دانشکده مهندسی برق و کامپیوتر، دانشگاه تبریز، تبریز، ایران | ||
چکیده | ||
رهگیری بصری شی دلخواه یک موضوع اساسی و چالش برانگیز در حوزه بینایی ماشین است که بهطور سنتی توسط در نظر گرفتن یک مدل برای هدف و با استفاده از دادههای آموزشی همان ویدیو انجام شده است. اکثر رهگیرها بهسختی میتوانند با در نظر گرفتن ویژگیهای برخط و بیدرنگ در صدر مقایسه نتایج مشهورترین روشها قرار گیرند. در این مقاله یک چارچوب رهگیری بر اساس شبکه سیامی ارائه شده که یادگیری رهگیر بهصورت برخط و فرآیند رهگیری بیدرنگ بوده و نام آن STD-Siam است. از آنجا که شبکه سیامی دارای محدودیت آموزش برخط است و مدت طولانی نمیتواند چالشهای موجود در رهگیری را مدیریت کند، هدف STD-Siam از راهگزین بین رهگیر سنتی و رهگیر بر مبنای یادگیری ژرف، تعلیم هر دو رهگیر با هدف رفع ابهام بین هدف و پسزمینه در هر فرنامه دلخواه است. ابتدا از طریق رهگیر سنتی دادههای آموزشی تولید شده، سپس این دادهها با فن برافزایی گسترش داده میشوند تا شبکه ژرف به خوبی آموزش بیند. این روش میتواند با سرعت 66 فریمدرثانیه اجرا شود و نسبت به الگوریتمهای مشابه فعلی با وجود سادگی آن نتایج خوبی را بهدست آورد و بهصورت طولانی مدت هدف را رهگیری کند. این سرعت رهگیری فراتر از بیدرنگ ( بیش از 30 فریم در ثانیه) بهواسطه آشکارساز برجستگی در حوزه فرکانس است که نامزدهای انتخابی هدف بهطور دقیق محاسبه شده و از روبش کل تصویر بهصورت کورکورانه جلوگیری میشود تا بار محاسباتی کاهش یابد. | ||
کلیدواژهها | ||
رهگیری بصری طولانی مدت؛ شبکه پیچشی سیامی؛ یادگیری ژرف | ||
مراجع | ||
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آمار تعداد مشاهده مقاله: 141 تعداد دریافت فایل اصل مقاله: 60 |