A scale and orientation adaptive mean shift tracking (SOAMST) algorithm is proposed in this study to address the problem of how to estimate the scale and orientation changes of the target under the mean shift tracking framework. In the original mean shift tracking algorithm, the position of the target can be well estimated, whereas the scale and orientation changes cannot be adaptively estimated. Considering that the weight image derived from the target model and the candidate model can represent the possibility that a pixel belongs to the target, the authors show that the original mean shift tracking algorithm can be derived using the zeroth- and the first-order moments of the weight image. With the zeroth-order moment and the Bhattacharyya coefficient between the target model and candidate model, a simple and effective method is proposed to estimate the scale of target. Then an approach, which utilises the estimated area and the second-order centre moment, is proposed to adaptively estimate the width, height and orientation changes of the target. Extensive experiments are performed to testify the proposed method and validate its robustness to the scale and orientation changes of the target.

Did you like this research project?

To get this research project Guidelines, Training and Code... Click Here

PROJECT TITLE : Large Scale Tensor Factorization via Parallel Sketches ABSTRACT: In recent years, tensor factorization methods have seen a rise in their level of popularity. Tensors are appealing for a number of reasons, one of
PROJECT TITLE : Optimal Scale Combination Selection Integrating Three-Way Decision With Hasse Diagram ABSTRACT: In the field of machine learning, the multi-scale decision system, also known as MDS, is a useful tool for describing
PROJECT TITLE : Large-Scale Affine Matrix Rank Minimization With a Novel Nonconvex Regularizer ABSTRACT: The goal of low-rank minimization is to recover a matrix with the lowest possible rank while still satisfying the constraints
PROJECT TITLE : Group Sampling for Scale Invariant Face Detection ABSTRACT: For the sake of efficiency, detectors that are based on deep learning have a tendency to detect objects of multiple scales within a single input image.
PROJECT TITLE : Blockchain Scaling using Rollups A Comprehensive Survey ABSTRACT: In recent years, blockchain systems have experienced significant expansion as a direct result of the enormous potential offered by the technology

Ready to Complete Your Academic MTech Project Work In Affordable Price ?

Project Enquiry