ABSTRACT:

The background-weighted histogram (BWH) algorithm proposed by Comaniciu et al. attempts to reduce the interference of background in target localisation in mean-shift tracking. However, the authors prove that the weights assigned to pixels in the target candidate region by BWH are proportional to those without background information, that is, BWH does not introduce any new information because the mean-shift iteration formula is invariant to the scale transformation of weights. Then a corrected BWH (CBWH) formula is proposed by transforming only the target model but not the target candidate model. The CBWH scheme can effectively reduce background??s interference in target localisation. The experimental results show that CBWH can lead to faster convergence and more accurate localisation than the usual target representation in mean-shift tracking. Even if the target is not well initialised, the proposed algorithm can still robustly track the object, which is hard to achieve by the conventional target representation.


Did you like this research project?

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


PROJECT TITLE : Robust Fuzzy Learning for Partially Overlapping Channels Allocation in UAV Communication Networks ABSTRACT: The emerging cellular-enabled unmanned aerial vehicle (UAV) communication paradigm poses significant challenges
PROJECT TITLE : Server-Aided Fine-Grained Access Control Mechanism with Robust Revocation in Cloud Computing ABSTRACT: In a wide variety of cloud computing applications, attribute based encryption, also known as ABE, makes it
PROJECT TITLE : Robust H∞ Network Observer-Based Attack-Tolerant Path Tracking Control of Autonomous Ground Vehicle ABSTRACT: Under the influence of external disturbance, measurement noise, and actuator/sensor attack signals,
PROJECT TITLE : Robust Localization System using Vector Combination in Wireless Sensor Networks ABSTRACT: In this paper, we propose a localization system that is based on vectors and that takes into account both distance and
PROJECT TITLE : Robust Variational Learning for Multiclass Kernel Models With Stein Refinement ABSTRACT: The ability of kernel-based models to generalize well is impressive, but the vast majority of them, including the SVM, are

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

Project Enquiry