GPU in comparison to nearly 2400 ms for a 16-threaded CPU version) without degradation in feature extraction performance, our work expands the applicability of the KAZE algorithm. Additionally, the strategies described here could also prove useful for the GPU implementation of other nonlinear scale-space-based image processing algorithms.by B. Ramkumar, Rob Laber, Hristo Bojinov and Ravi Sadananda Hegd
This thesis explores the possibility of utilizing Graphics Processing Units (GPUs) to address the co...
This paper presents a method that takes advantage of powerful graphics hardware to obtain fully affi...
In computer vision, silhouette extraction plays an important role. Many applications need to extract...
This paper proposes a real-time feature extraction VLSI architecture for high-resolution images bas...
Computer vision algorithms, such as scale-invariant feature transform (SIFT), are used in many impor...
Abstract—In this paper, we construe key factors in design and evaluation of image processing algorit...
The motivation of this research is to prove that GPUs can provide significant speedup of long-execut...
High speed feature point detection and tracking is very demanding for many realtime computer vision ...
Ever since the introduction of freely programmable hardware components into modern graphics hardware...
Majority of current mobile devices include a camera. To meet the form-factor and price requirements,...
Abstract—Graphics processing units (GPUs) are capable of achieving remarkable performance improvemen...
Abstract: Scale-invariant feature transform (SIFT) was an algorithm in computer vision to detect and...
Image feature extraction is instrumental for most of the best-performing algorithms in computer vis...
Image amplification is an important image enhancement technique for applications such as medicine, s...
This article presents a fully functional GPU-based implementation of Scale Invariant Feature Transfo...
This thesis explores the possibility of utilizing Graphics Processing Units (GPUs) to address the co...
This paper presents a method that takes advantage of powerful graphics hardware to obtain fully affi...
In computer vision, silhouette extraction plays an important role. Many applications need to extract...
This paper proposes a real-time feature extraction VLSI architecture for high-resolution images bas...
Computer vision algorithms, such as scale-invariant feature transform (SIFT), are used in many impor...
Abstract—In this paper, we construe key factors in design and evaluation of image processing algorit...
The motivation of this research is to prove that GPUs can provide significant speedup of long-execut...
High speed feature point detection and tracking is very demanding for many realtime computer vision ...
Ever since the introduction of freely programmable hardware components into modern graphics hardware...
Majority of current mobile devices include a camera. To meet the form-factor and price requirements,...
Abstract—Graphics processing units (GPUs) are capable of achieving remarkable performance improvemen...
Abstract: Scale-invariant feature transform (SIFT) was an algorithm in computer vision to detect and...
Image feature extraction is instrumental for most of the best-performing algorithms in computer vis...
Image amplification is an important image enhancement technique for applications such as medicine, s...
This article presents a fully functional GPU-based implementation of Scale Invariant Feature Transfo...
This thesis explores the possibility of utilizing Graphics Processing Units (GPUs) to address the co...
This paper presents a method that takes advantage of powerful graphics hardware to obtain fully affi...
In computer vision, silhouette extraction plays an important role. Many applications need to extract...