We study the domain of dominant competence of six popular classifiers in a space of data complexity measurements. We observe that the simplest classifiers, nearest neighbor and li...
This paper describes an online learning method of color transformation for interactive object recognition. In order to recognize objects under various lighting conditions, the sys...
Robotic navigation algorithms increasingly make use of the panoramic field of view provided by omnidirectional images to assist with localization tasks. Since the images taken by ...
The front end of many motion analysis algorithms is usually a process that generates bounding boxes around each moving object, roughly segmenting the objects from the background. ...
The paper presents a robust digital image watermarking scheme that uses both the characteristics of the human visual system (HVS) and statistical information measure. Spread trans...
The Scanning N-Tuple classifier (SNT) is a fast and accurate method for classifying sequences. Applications include both on-line and off-line hand-written character recognition. S...
In augmented virtuality, estimating object surface reflectance properties is important when rendering objects under arbitrary illuminationconditions. However, faithfully estimatin...
In an experiment with a soccer playing robot, periodic temporally-constrained nonlinear principal component neural networks (NLPCNNs) are shown to characterize humanoid motion eff...
Karl F. MacDorman, Rawichote Chalodhorn, Minoru As...
The performance of face recognition systems that use twodimensional (2D) images is dependent on consistent conditions such as lighting, pose and facial expression. We are developi...
The efficiency of three tracking reliability metrics based on information theory and normalized correlation is examined in this paper. The two information theory tools used for th...