هدف ما ردیابی شی توسط آنالیز حداقل مربعات ذره ای و پیاده سازی در متلب

We propose an object tracking algorithm that learns a set of appearance models for adaptive discriminative object representation. In this paper, object tracking is posed as a binary classification problem in which the correlation of object appearance and class labels from foreground and background is modeled by partial least squares (PLS) analysis, for generating a low-dimensional discriminative feature subspace. As object appearance is temporally correlated and likely to repeat over time, we learn and adapt multiple appearance models with PLS analysis for robust tracking.

Object Tracking via Partial Least Squares Analysis

ردیابی شی توسط آنالیز حداقل مربعات ذره ای

Published in: IEEE Transactions On Image Processing

Date of Publication: VOL. 21, NO. 10, OCTOBER 2012

مشخصات نویسنده:

کارشناسی ارشد مخابرات سیستم

دانشگاه علم و صنعت ایران

محتویات

• سورس کد متلب
• مقاله اصلی

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