In this paper, we present a probabilistic framework for automatic detection and tracking of objects. We address the data association problem by formulating the visual tracking as ...
This paper proposes a license plate detection algorithm using both global statistical features and local Haar-like features. Classifiers using global statistical features are cons...
This paper presents a novel line-based affine invariant object location methodology. Our algorithm employs a new line-based transformation space decomposition technique to exploit...
Recently, some linear approaches to camera calibration from sphere images are proposed. In this paper, a novel linear approach is proposed by exploiting the identity constraint on...
This study applies Auto Regressive (AR) and Auto Regressive Moving Average (ARMA) modeling to wavelet decomposed terahertz pulsed signals to assist biomedical diagnosis and mail/p...
Bradley Ferguson, Brian Wai-Him Ng, Derek Abbott, ...
A novel approach of combining cepstral features and prosodic features in language identification is presented in this paper. This combination approach shows a significant improvem...
1 A kernel determines the inductive bias of a learning algorithm on a specific data set, and it is beneficial to design specific kernel for a given data set. In this work, we propo...
We describe a new omnidirectional stereo imaging system that uses a concave lens and a convex mirror to produce a stereo pair of images on the sensor of a conventional camera. The...
We propose a method of calibrating multiple camera systems that operates by adjusting the camera parameters and the 3D shape of objects onto silhouette observations. Our method em...
This paper presents an experimental study on automatic face gender classification by building a system that mainly consists of four parts, face detection, face alignment, texture ...