This paper introduces a semi-supervised distance metric learning algorithm which uses pair-wise equivalence (similarity and dissimilarity) constraints to improve the original dist...
Driver assistance helps save lives. Accurate 3D pose is required to establish if a traffic sign is relevant to the driver. We propose a real-time system that integrates single vi...
Victor Adrian Prisacariu, Radu Timofte, Karel Zimm...
In this paper, we propose a probabilistic method to model the dynamic traffic flow across nonoverlapping camera views. By assuming the transition time of object movement follows a...
—This article proposes a general extension of the Error Correcting Output Codes (ECOC) framework to the online learning scenario. As a result, the final classifier handles the ...
Sergio Escalera, David Masip, Eloi Puertas, Petia ...
In this paper we develop a probabilistic interpretation and a full Bayesian inference for non-negative matrix deconvolution (NMFD) model. Our ultimate goal is unsupervised extract...
This paper is concerned with accuracy estimation of point trajectories in video sequences without ground truth information. This is an essential problem for many computer vision a...
We propose a learning method for gait synthesis from a sequence of shapes(frames) with the ability to extrapolate to novel data. It involves the application of PCA, first to redu...
Muayed Sattar Al-Huseiny, Sasan Mahmoodi, Mark Nix...
Finding point correspondences which are consistent with a geometric constraint is one of the cornerstones of many computer vision problems. This is a difficult task because of sp...
The Gaussian Mixture Model (GMM) is often used in conjunction with Mel-frequency cepstral coefficient (MFCC) feature vectors for speaker recognition. A great challenge is to use ...
Matching near-infrared (NIR) face images to visible light (VIS) face images offers a robust approach to face recognition with unconstrained illumination. In this paper we propose ...