An augmented Lagrangian method for total variation video restoration,”

Abstract-This paper presents a fast algorithm for restoring video sequences. The proposed algorithm, as opposed to existing methods, does not consider video restoration as a sequence of image restoration problems. Rather, it treats a video sequence as a space-time volume and poses a space-time total variation regularization to enhance the smoothness of the solution. The optimization problem is solved by transforming the original unconstrained minimization problem to an equivalent constrained minimization problem. An augmented Lagrangian method is used to handle the constraints, and an alternating direction method (ADM) is used to iteratively find solutions of the subproblems. The proposed algorithm has a wide range of applications, including video deblurring and denoising, video disparity refinement, and hot-air turbulence effect reduction

Составление композиций из поверхностно активных веществ для устранения асфальтенопарофиновых отложений

International audienceWe present SLAPbook, an application using SLAP, translucent and tangible widgets for use on vision-based multi-touch tabletops in Single Display Groupware (SDG) environments. SLAP stands for Silicone ILluminated Active Peripherals and includes widgets such as sliders, knobs, keyboards, and buttons. The widgets add tactile feedback to multi-touch tables while simultaneously providing dynamic relabeling to tangible objects using the table's rear projection. SLAPbook provides multiple users the ability to add and edit content to a guestbook, browse other peoples' entries, and access personal data using a token-based personalization system. Interaction with the table takes place in the personal and public space so that users can make use of personal and shared controls to perform separate and coordinative actions

Revolutionizing laparoscopy : bringing glasses-free multiview 3D into the operating room

Over the past several years, a dramatic increase in attention has been paid to 3D media, particularly in the movie industry. Due to the lack of previous algorithmic advancement and the absence of unobtrusive technology, however, three-dimensional visualization has failed to penetrate the operating room until now. In this work, we present a system to deliver glasses-free 3D visualization of laparoscopic surgeries to the operating room via multiview autostereoscopic displays. We begin by developing robust stereo-to-multiview content generation so that we may produce an arbitrary number of stereo sequences for presentation on autostereoscopic displays. We then introduce a reliable disparity estimation technique that enables the synthesis of the virtual views. In addition, we enforce spatio-temporal consistency in disparity estimates to provide a superior 3D experience for surgeons and operating room staff. Finally, we implement the entire system on graphics hardware in order to achieve real-time operability. Numerous attempts have been made to introduce three-dimensional (3D) video systems into clinical routine, particularly for surgeries. The drawback with all of them thus far has been the fact that they require users to wear cumbersome glasses in order to receive the advantage of stereoscopy. In this work, we present, to our best knowledge, the world's first laparoscopic surgical system that delivers glasses-free multiview 3D in high-denition (HD) resolution. In addition to a quantitative evaluation of the video processing components, we performed an initial subjective study with laparoscopically experienced surgeons, which yielded very promising result

Sampling-based Robust Multi-lateral Filter for Depth Enhancement

Publication in the conference proceedings of EUSIPCO, Bucharest, Romania, 201

Spatio-temporal consistency in video disparity estimation

We present a novel stereo video disparity estimation method. The proposed method is a two-stage algorithm. During the first stage, initial disparity maps are computed in a frame-by-frame basis. In the second stage, the initial estimates are treated as a space-time volume. By setting up an l1-normed minimization problem with a novel three-dimensional total variation regularization, spatial smoothness and temporal consistency are handled simultaneously. Due to our unique formulation, any existing image disparity estimation tech-nique may utilize our method as a post-processing step to refine noisy estimates or to be extended to videos. The proposed method shows superior speed, accuracy, and con-sistency compared to state-of-the-art algorithms. Index Terms — stereo vision, video disparity, signal de-noising, augmented Lagrangian, total variation minimization 1

Efficient stereo-to-multiview synthesis

From a rectified stereo image pair, the task of view synthesis is to generate images from any viewpoint along the baseline. The main difficulty of the problem is how to fill occluded regions. In this pa-per, we present a new method for view synthesis that is both fast and accurate. Occlusions are filled using color and disparity informa-tion to produce consistent pixel estimates. Results are comparable to current state-of-the-art methods in terms of objective measures while computation time is drastically reduced. This work has appli-cations in free-viewpoint television, angular scalability for 3D video coding/decoding, and stereo-to-multiview conversion. Index Terms — 3D, occlusion, view interpolation. 1