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 present a hybrid approach to image watermarking that exploits results from both information theory and perceptual studies. Towards this purpose we use a waterfilling-type algor...
Segmentation and tracking of objects in video sequences is important for a number of applications. In the supervised variant, segmentation can be achieved by modelling the probabi...
We develop a new approach to image denoising based on complexity regularization. This technique presents a flexible alternative to the more conventional l2 , l1 , and Besov regula...
In this paper, we present a novel method for model estimation for visual servoing. This method employs a particle filter algorithm to estimate the depth of the image features onli...