We studies the effects of the tracking system caused by object’s sudden variable motion in order to improve the system’s performance and efficiency. Our approach combines the strengths of two successful algorithms: sum-of-squared differences(SSD) and kernel particle filters(KPF) which was developed from usual particle filters. In cascaded algorithm SKPF, both of them can exert their
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We studies the effects of the tracking system caused by object’s sudden variable motion in order to improve the system’s performance and efficiency. Our approach combines the strengths of two successful algorithms: sum-of-squared differences(SSD) and kernel particle filters(KPF) which was developed from usual particle filters. In cascaded algorithm SKPF, both of them can exert their
(Read More…)
We studies the effects of the tracking system caused by object’s sudden variable motion in order to improve the system’s performance and efficiency. Our approach combines the strengths of two successful algorithms: sum-of-squared differences(SSD) and kernel particle filters(KPF) which was developed from usual particle filters. In cascaded algorithm SKPF, both of them can exert their
(Read More…)
We studies the effects of the tracking system caused by object’s sudden variable motion in order to improve the system’s performance and efficiency. Our approach combines the strengths of two successful algorithms: sum-of-squared differences(SSD) and kernel particle filters(KPF) which was developed from usual particle filters. In cascaded algorithm SKPF, both of them can exert their
(Read More…)
We studies the effects of the tracking system caused by object’s sudden variable motion in order to improve the system’s performance and efficiency. Our approach combines the strengths of two successful algorithms: sum-of-squared differences(SSD) and kernel particle filters(KPF) which was developed from usual particle filters. In cascaded algorithm SKPF, both of them can exert their
(Read More…)
We studies the effects of the tracking system caused by object’s sudden variable motion in order to improve the system’s performance and efficiency. Our approach combines the strengths of two successful algorithms: sum-of-squared differences(SSD) and kernel particle filters(KPF) which was developed from usual particle filters. In cascaded algorithm SKPF, both of them can exert their
(Read More…)
We studies the effects of the tracking system caused by object’s sudden variable motion in order to improve the system’s performance and efficiency. Our approach combines the strengths of two successful algorithms: sum-of-squared differences(SSD) and kernel particle filters(KPF) which was developed from usual particle filters. In cascaded algorithm SKPF, both of them can exert their
(Read More…)
Detection and tracking of moving objects is an important project in the field of computer vision, which is applied widely in intelligent video monitoring, human-computer interaction based on video, vision-guided robot, virtual reality, automatic transmission, etc.This thesis has researched detecting and tracking technique of moving objects.On the basis of analyzing the principle and property of
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Mean Shift is a very good algorithm in visual target tracking area. Many scholars in foreign countries has developed this algorithm in recent years, however, few scholars study it in our country. A few articles can be found last year ever.I experienced many difficulties, when I entered the realm of target tracking. Finally I found
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