مشاهده مشخصات مقاله
Feature integration for adaptive visual tracking in a particle filtering framework
|
Authors |
-
M. Komeili
-
N. Armanfard
-
M. Valizadeh
-
E. Kabir
|
|
Conference |
چهاردهمین کنفرانس بینالمللی سالانه انجمن کامپیوتر ایران |
|
Abstract |
In this paper we propose a new integration method for
multi-feature object tracking in a particle filter
framework. We divide particles into separate clusters.
All particles within a cluster measure a specific
feature. The number of particles within a cluster is in
proportion to the reliability of associated feature. We
do a compensation stage which neutralizes the effect of
particles weights mean within a cluster. Compensation
stage balances the concentration of particles around
local maximal. So, particles are distributed more
effectively in the scene. Proposed method provides
both effective hypothesis generation and effective
evaluation of hypothesis. Experimental results over a
set of real-world sequences demonstrate better
performance of our method compared to the common
methods of feature integration. |
|
قیمت |
-
برای اعضای سایت : 100,000 Rial
-
برای دانشجویان عضو انجمن : 20,000 Rial
-
برای اعضای عادی انجمن : 40,000 Rial
|
خرید مقاله
|
|
.gif){kind=icon}