We propose a content based video retrieval system in some main steps resulting in a good performance. From a main video, we process extracting keyframes and principal objects using Segmentation of Aggregating Superpixels (SAS) algorithm. After that, Speeded Up Robust Features (SURF) are selected from those principal objects. Then, the model “Bag-of-words” in accompanied by SVM classification are applied to obtain the retrieval result. Our system is evaluated on over 300 videos in diversity from music, history, movie, sports, and natural scene to TV program show. | TRƯỜNG ĐẠI HỌC SƯ PHẠM TP HỒ CHÍ MINH TẠP CHÍ KHOA HỌC HO CHI MINH CITY UNIVERSITY OF EDUCATION JOURNAL OF SCIENCE KHOA HỌC TỰ NHIÊN VÀ CÔNG NGHỆ NATURAL SCIENCES AND TECHNOLOGY ISSN: 1859-3100 Tập 14, Số 9 (2017): 24-33 Vol. 14, No. 9 (2017): 24-33 Email: tapchikhoahoc@; Website: CONTENT BASED VIDEO RETRIEVAL SYSTEM USING PRINCIPAL OBJECT ANALYSIS Bui Van Thinh1 , Tran Anh Tuan1, Ngo Quoc Viet2*, Pham The Bao1 1 2 University of Science Ho Chi Minh City Ho Chi Minh City University of Education Received: 25/7/2017; Revised: 04/9/2017; Accepted: 23/9/2017 Bui Van Thinh+, Tran Anh Tuan+, Ngo Quoc Viet* and Pham The Bao+ ABSTRACT Video retrieval is a searching problem on videos or clips based on the content of video clips which relates to the input image or video. Some recent approaches have been in challenging problem due to the diversity of video types, frame transitions and camera positions. Besides, that an appropriate measures is selected for the problem is a question. We propose a content based video retrieval system in some main steps resulting in a good performance. From a main video, we process extracting keyframes and principal objects using Segmentation of Aggregating Superpixels (SAS) algorithm. After that, Speeded Up Robust Features (SURF) are selected from those principal objects. Then, the model “Bag-of-words” in accompanied by SVM classification are applied to obtain the retrieval result. Our system is evaluated on over 300 videos in diversity from music, history, movie, sports, and natural scene to TV program show. Keywords: Video retrieval, principal objects, keyframe, Segmentation of Aggregating Superpixels, SURF, Bag-of-words, SVM. TÓM TẮT Hệ thống truy vấn video dựa trên nội dung sử dụng phân tích thành phần chính Truy vấn video nhằm tìm kiếm nội dung trong video hoặc clip gần giống với với ảnh hoặc video đầu vào. Một số thách thức khi thực hiện bài toán này bao gồm sự đa dạng của kiểu video, chuyển .
