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ICRA
2010
IEEE
164views Robotics» more  ICRA 2010»
13 years 6 months ago
Boundary detection based on supervised learning
— Detecting the boundaries of objects is a key step in separating foreground objects from the background, which is useful for robotics and computer vision applications, such as o...
Kiho Kwak, Daniel F. Huber, Jeongsook Chae, Takeo ...
CRV
2011
IEEE
268views Robotics» more  CRV 2011»
12 years 7 months ago
Feature Tracking Evaluation for Pose Estimation in Underwater Environments
—In this paper we present the computer vision component of a 6DOF pose estimation algorithm to be used by an underwater robot. Our goal is to evaluate which feature trackers enab...
Florian Shkurti, Ioannis M. Rekleitis, Gregory Dud...
ARCS
2005
Springer
14 years 1 months ago
Self-Organizing, Adaptive Data Fusion for 3d Object Tracking
Data fusion concepts are a necessary basis for utilizing complex networks of sensors. A key feature for a robust data fusion system is adaptivity, both to be fault-tolerant and to...
Olaf Kähler, Joachim Denzler
CIKM
2010
Springer
13 years 6 months ago
CiteData: a new multi-faceted dataset for evaluating personalized search performance
Personalized search systems have evolved to utilize heterogeneous features including document hyperlinks, category labels in various taxonomies and social tags in addition to free...
Abhay Harpale, Yiming Yang, Siddharth Gopal, Daqin...
ICPR
2008
IEEE
14 years 2 months ago
Improvement on Mean Shift based tracking using second-order information
Object tracking based on Mean Shift (MS) algorithm has been very successful and thus receives significant research interests. Unfortunately, traditional MS based tracking only ut...
Lijuan Xiao, Peihua Li