A New Target Tracking Scheme Based on Improved Mean Shift and Adaptive Kalman Filter

نویسندگان

  • Shangbo Zhou
  • Peng Hu
  • Kun Li
  • Yujiong Liu
چکیده

In this paper, a target tracking algorithm is proposed by combining the improved Mean Shift algorithm with the adaptive Kalman filter. For a selected moving object, frame difference and region growing methods are used to segment target and extract the dominant color. In the tracking process, the initial iterative position is obtained by adaptive Kalman filter in each frame. The tracking result obtained by improved Mean Shift is fed back to adaptive Kalman filter as the measurement for correction. The estimate parameters of adaptive Kalman filter will be adjusted by occlusion ratio adaptively. Experimental results indicate that the proposed algorithm can detect and track the moving object consecutively and effectively in video and have stronger robustness for occlusion.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Doppler and bearing tracking using fuzzy adaptive unscented Kalman filter

The topic of Doppler and Bearing Tracking (DBT) problem is to achieve a target trajectory using the Doppler and Bearing measurements. The difficulty of DBT problem comes from the nonlinearity terms exposed in the measurement equations. Several techniques were studied to deal with this topic, such as the unscented Kalman filter. Nevertheless, the performance of the filter depends directly on the...

متن کامل

A New Modified Particle Filter With Application in Target Tracking

The particle filter (PF) is a novel technique that has sufficiently good estimation results for the nonlinear/non-Gaussian systems. However, PF is inconsistent that caused mainly by loss of particle diversity in resampling step and unknown a priori knowledge of the noise statistics. This paper introduces a new modified particle filter called adaptive unscented particle filter (AUPF) to overcome th...

متن کامل

A New Adaptive Extended Kalman Filter for a Class of Nonlinear Systems

This paper proposes a new adaptive extended Kalman filter (AEKF) for a class of nonlinear systems perturbed by noise which is not necessarily additive. The proposed filter is adaptive against the uncertainty in the process and measurement noise covariances. This is accomplished by deriving two recursive updating rules for the noise covariances, these rules are easy to implement and reduce the n...

متن کامل

Adaptive Fusion of Inertial Navigation System and Tracking Radar Data

Against the range-dependent accuracy of the tracking radar measurements including range, elevation and bearing angles, a new hybrid adaptive Kalman filter is proposed to enhance the performance of the radar aided strapdown inertial navigation system (INS/Radar). This filter involves the concept of residual-based adaptive estimation and adaptive fading Kalman filter and tunes dynamically the fil...

متن کامل

Kernel Bandwidth Adaptive Target Tracking Algorithm Based on Mean - Shift

The kernel bandwidth of the classical Mean-Shift tracking algorithm is fixed, and it usually results in tracking failure when the target’s size changes. A kernel bandwidth adaptive Mean-Shift tracking algorithm is presented with frame difference method to solve the question in this paper. According to the targets’ size obtained from the inter-frame difference method, the bandwidth matrix of ker...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2012