In this paper we evaluate the effectiveness of two likelihood normalization techniques, the Background Model Set (BMS) and the Universal Background Model (UBM), for improving perf...
We develop a mixture-based approach to robust density modeling and outlier detection for experimental multivariate data that includes measurement error information. Our model is d...
This paper presents a multi-view articulated human motion tracking framework using particle filter with manifold learning through Gaussian process latent variable model. The dime...
We develop a biologically motivated oscillatory network model and related dynamical synchronizationbased method of image segmentation. The first version of successive segmentation...
Image-Adaptive watermarking systems exploit visual models to adapt the watermark to local properties of the host image. This leads to a watermark power enhancement, hence an improv...