Fast mean shift by compact density representation
The Mean Shift procedure is a well established clustering technique that is widely used in
imaging applications such as image and video segmentation, denoising, object tracking …
imaging applications such as image and video segmentation, denoising, object tracking …
Event-based color segmentation with a high dynamic range sensor
This paper introduces a color asynchronous neuromorphic event-based camera and a
methodology to process color output from the device to perform color segmentation and …
methodology to process color output from the device to perform color segmentation and …
A robust pedestrian detection approach based on shapelet feature and Haar detector ensembles
W Yao, Z Deng - Tsinghua Science and Technology, 2012 - ieeexplore.ieee.org
Detection of pedestrians in images and video sequences is important for many applications
but is very challenging due to the various silhouettes of pedestrians and partial occlusions …
but is very challenging due to the various silhouettes of pedestrians and partial occlusions …
An implementation of the mean shift filter on fpga
DBK Trieu, T Maruyama - 2011 21st international conference …, 2011 - ieeexplore.ieee.org
Mean shift algorithm is a procedure which is often used for color image segmentation. Its
computational cost, however, is very high, and many techniques for reducing the cost have …
computational cost, however, is very high, and many techniques for reducing the cost have …
High-resolution image segmentation using fully parallel mean shift
B Varga, K Karacs - EURASIP Journal on Advances in Signal Processing, 2011 - Springer
In this paper, we present a fast and effective method of image segmentation. Our design
follows the bottom-up approach: first, the image is decomposed by nonparametric clustering; …
follows the bottom-up approach: first, the image is decomposed by nonparametric clustering; …
Fast integral meanshift: application to color segmentation of document images
F LeBourgeois, F Drira, D Gaceb… - 2013 12th International …, 2013 - ieeexplore.ieee.org
Global Mean Shift algorithm is an unsupervised clustering technique already applied for
color document image segmentation. Nevertheless, its important computational cost limits its …
color document image segmentation. Nevertheless, its important computational cost limits its …
KDE paring and a faster mean shift algorithm
The kernel density estimate (KDE) is a nonparametric density estimate which has broad
application in computer vision and pattern recognition. In particular, the mean shift …
application in computer vision and pattern recognition. In particular, the mean shift …
Real-time color image segmentation based on mean shift algorithm using an FPGA
DBK Trieu, T Maruyama - Journal of real-time image processing, 2015 - Springer
Image segmentation is one of the most important tasks in the image processing, and mean
shift algorithm is often used for color image segmentation because of its high quality. The …
shift algorithm is often used for color image segmentation because of its high quality. The …
A monocular vision based pedestrian detection system for intelligent vehicles
L Yu, W Yao, H Liu, F Liu - 2008 IEEE Intelligent Vehicles …, 2008 - ieeexplore.ieee.org
Detecting pedestrians in images is a challenging task, especially for the intelligent vehicle
environment where there is a moving camera. In this paper, we develop a monocular vision …
environment where there is a moving camera. In this paper, we develop a monocular vision …
Preserving data distribution in sampling and instance selection with Renyi's divergence
This paper introduces a novel method for sampling based on a distribution function. By
utilizing Renyi's divergence criterion, a recursive formulation is derived directly from the …
utilizing Renyi's divergence criterion, a recursive formulation is derived directly from the …