Video Copy Detection on the Internet: The Challenges of Copyright and Multiplicity

This paper presents applications for dealing with videos on the web, using an efficient technique for video copy detection in large archives. Managing videos on the web is the source of two exciting challenges: the respect of the copyright and the linkage of multiple videos. We present a technique called ViCopT for Video Copy Tracking which is based on labels of behavior of local descriptors computed along video. The re-sults obtained on large amount of data (270 hours of videos from the Internet) are very promising, even with a large video database (700 hours): ViCopT displays excellent robustness to various severe signal transformations, making it able to identify copies accurately from highly similar videos, as well as to link similar videos, in order to reduce redundancy or to gather the metadata associated. Finally, we also show that ViCopT goes further by detecting segments having the same background, with the aim of linking videos of the same cate-gory, like forecast weather programs or particular TV shows. 1

Labelling the Behaviour of Local Descriptors for Selective Video Content Retrieval

This paper presents an approach for indexing a large set of videos by considering the cinematic behaviour of local visual features along the sequences. The proposed concept is based on the extraction and the local description of interest points and further on the estimation of their trajectories along the video sequence. Analysing the low-level description obtained allows to highlight semantic trends of behaviours and then to assign labels. Such an indexing approach of the video content has several interesting properties: the low-level description provides a rich and compact description, while labels of behaviour provide a generic and semantic description, relevant for selective video content retrieval depending on the application. The approach is firstly evaluated for Content-Based Copy Detection. We show that taking these labels into account allows to significantly reduce false alarms. Secondly, the approach is experimented on particular applications of video monitoring, where selective labels of behaviour show their capability to improve the analysis and the retrieval of spatio-temporal video content

Surgical site infection after gastrointestinal surgery in high-income, middle-income, and low-income countries: a prospective, international, multicentre cohort study

Background: Surgical site infection (SSI) is one of the most common infections associated with health care, but its importance as a global health priority is not fully understood. We quantified the burden of SSI after gastrointestinal surgery in countries in all parts of the world. Methods: This international, prospective, multicentre cohort study included consecutive patients undergoing elective or emergency gastrointestinal resection within 2-week time periods at any health-care facility in any country. Countries with participating centres were stratified into high-income, middle-income, and low-income groups according to the UN's Human Development Index (HDI). Data variables from the GlobalSurg 1 study and other studies that have been found to affect the likelihood of SSI were entered into risk adjustment models. The primary outcome measure was the 30-day SSI incidence (defined by US Centers for Disease Control and Prevention criteria for superficial and deep incisional SSI). Relationships with explanatory variables were examined using Bayesian multilevel logistic regression models. This trial is registered with ClinicalTrials.gov, number NCT02662231. Findings: Between Jan 4, 2016, and July 31, 2016, 13 265 records were submitted for analysis. 12 539 patients from 343 hospitals in 66 countries were included. 7339 (58·5%) patient were from high-HDI countries (193 hospitals in 30 countries), 3918 (31·2%) patients were from middle-HDI countries (82 hospitals in 18 countries), and 1282 (10·2%) patients were from low-HDI countries (68 hospitals in 18 countries). In total, 1538 (12·3%) patients had SSI within 30 days of surgery. The incidence of SSI varied between countries with high (691 [9·4%] of 7339 patients), middle (549 [14·0%] of 3918 patients), and low (298 [23·2%] of 1282) HDI (p < 0·001). The highest SSI incidence in each HDI group was after dirty surgery (102 [17·8%] of 574 patients in high-HDI countries; 74 [31·4%] of 236 patients in middle-HDI countries; 72 [39·8%] of 181 patients in low-HDI countries). Following risk factor adjustment, patients in low-HDI countries were at greatest risk of SSI (adjusted odds ratio 1·60, 95% credible interval 1·05–2·37; p=0·030). 132 (21·6%) of 610 patients with an SSI and a microbiology culture result had an infection that was resistant to the prophylactic antibiotic used. Resistant infections were detected in 49 (16·6%) of 295 patients in high-HDI countries, in 37 (19·8%) of 187 patients in middle-HDI countries, and in 46 (35·9%) of 128 patients in low-HDI countries (p < 0·001). Interpretation: Countries with a low HDI carry a disproportionately greater burden of SSI than countries with a middle or high HDI and might have higher rates of antibiotic resistance. In view of WHO recommendations on SSI prevention that highlight the absence of high-quality interventional research, urgent, pragmatic, randomised trials based in LMICs are needed to assess measures aiming to reduce this preventable complication

De la généricité à la sélectivité des descripteurs vidéo (application à la détection de copies par le contenu)

My PhD thesis presents a new approach for indexing large sets of videos by their content. The proposed concept is based on the extraction and the local description of different natures of points of interest and further on the estimation of their trajectories along the video sequence. Analyzing the low-level description obtained allows highlighting semantic labels of behaviors. Searching for copies in large video databases is a new critical issue. ViCopT is a system dedicated to video copy detection based on our video description. A complete evaluation on a large video database (1,000 hours) demonstrates the robustness and the discriminability of ViCopT and the relevance of our strategy. Comparative evaluations in European and international contexts present the high performances of our system facing other academic and industrial systems.Mes travaux de thèse portent sur l indexation et la recherche dans de grandes bases de vidéos. Partant d une description visuelle de l image basée sur plusieurs natures de points d intérêt, notre approche aboutit à une représentation de plus haut niveau, associant descripteurs visuels locaux, leurs trajectoires ainsi qu une interprétation en termes de comportement de ces descripteurs locaux au sein de la vidéo. Cette méthode permet une description fine de la vidéo tout en réduisant la redondance temporelle qui lui est intrinsèquement liée. Une application cruciale dans la gestion de patrimoines numériques est la traçabilité du catalogue vidéo. Dans ce contexte, nous proposons ViCopT, un système de détection de copie par le contenu. Une validationde sa robustesse et de sa discriminance a été réalisée sur une base de 1000h et a montrée la pertinence de nos choix. Les hautes performances de ViCopT ont été mesurées dans des évaluations comparatives tant au niveau européen qu'international.VERSAILLES-BU Sciences et IUT (786462101) / SudocSudocFranceF

VoxaleadNews: Robust Automatic Segmentation of Video into Browsable Content

International audienc

Local Behaviours Labelling for Content Based Video Copy Detection

International audienc

ViCopT: a robust system for content-based video copy detection in large databases

International audienc