Đang chuẩn bị liên kết để tải về tài liệu:
Báo cáo hóa học: " Object tracking system using a VSW algorithm based on color and point features"

Tuyển tập các báo cáo nghiên cứu về hóa học được đăng trên tạp chí hóa hoc quốc tế đề tài : Object tracking system using a VSW algorithm based on color and point features | Lim and Kang EURASIP Journal on Advances in Signal Processing 2011 2011 60 http asp.eurasipjournals.eom content 2011 1 60 o EURASIP Journal on Advances in Signal Processing a SpringerOpen Journal RESEARCH Open Access Object tracking system using a VSW algorithm based on color and point features Hye-Youn Lim and Dae-Seong Kang Abstract An object tracking system using a variable search window VSW algorithm based on color and feature points is proposed. A meanshift algorithm is an object tracking technique that works according to color probability distributions. An advantage of this algorithm based on color is that it is robust to specific color objects however a disadvantage is that it is sensitive to non-specific color objects due to illumination and noise. Therefore to offset this weakness it presents the VSW algorithm based on robust feature points for the accurate tracking of moving objects. The proposed method extracts the feature points of a detected object which is the region of interest ROI and generates a VSW using the given information which is the positions of extracted feature points. The goal of this paper is to achieve an efficient and effective object tracking system that meets the accurate tracking of moving objects. Through experiments the object tracking system is implemented that it performs more precisely than existing techniques. Keywords background modeling meanshift object tracking search window SIFT 1. Introduction The object tracking means tracing the progress of objects as they move over a sequence of images. Visual object tracking in complex environments is an important topic in the intelligent surveillance field. A good tracking algorithm should be able to work well in many real circumstances such as background clutters occlusions and different illuminations 1 2 . The object tracking methods can be divided into three groups according to feature values of the object which seems to be foreground color-based method boundarybased method and .