Output Constraint Transfer for Kernelized Correlation Filter in Tracking
نویسندگان
چکیده
منابع مشابه
Tracking in Aerial Hyperspectral Videos using Deep Kernelized Correlation Filters
Hyperspectral imaging holds enormous potential to improve the state-of-the-art in aerial vehicle tracking with low spatial and temporal resolutions. Recently, adaptive multi-modal hyperspectral sensors, controlled by Dynamic Data Driven Applications Systems (DDDAS) methodology, have attracted growing interest due to their ability to record extended data quickly from the aerial platforms. In thi...
متن کاملTarget Response Adaptation for Correlation Filter Tracking
The problem is convex quadratic and a stationary point is necessary and sufficient for global optimality. The following sections will discuss how Problem 1 is solved in the primal domain, dual domain, and for both single and multiple templates along with the formula used to generate the response map, whose maximum value determines the current detection. Lastly, we discuss a one way of incorpora...
متن کاملKernelized Bayesian Transfer Learning
Transfer learning considers related but distinct tasks defined on heterogenous domains and tries to transfer knowledge between these tasks to improve generalization performance. It is particularly useful when we do not have sufficient amount of labeled training data in some tasks, which may be very costly, laborious, or even infeasible to obtain. Instead, learning the tasks jointly enables us t...
متن کاملKernelized correlation tracker on smartphones
This paper shows the implementation of a KC tracker (high-speed kernelized correlation tracker) on an Android smartphone. The image processing part is implemented with the Android-NDK in C/C++. Some parts of the tracking algorithm, which can be parallelized very well, are partitioned and calculated on the GPU with OpenGL ES and OpenCL. Other parts, such as the Discrete Fourier Transform (DFT), ...
متن کاملEnKCF: Ensemble of Kernelized Correlation Filters for High-Speed Object Tracking
Computer vision technologies are very attractive for practical applications running on embedded systems. For such an application, it is desirable for the deployed algorithms to run in high-speed and require no offline training. To develop a single-target tracking algorithm with these properties, we propose an ensemble of the kernelized correlation filters (KCF), we call it EnKCF. A committee of...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IEEE Transactions on Systems, Man, and Cybernetics: Systems
سال: 2017
ISSN: 2168-2216,2168-2232
DOI: 10.1109/tsmc.2016.2629509