Related tools and services by the InVID parters
InVID Multimodal Analytics Dashboard
The InVID Multimodal Analytics Dashboard is a visual search and information exploration platform to identify and track evolving stories across multiple social media platforms – including participating actors (persons, organizations) and the relations among them. The dashboard uses multiple coordinated view technology for the desktop version, and a cross-platform HTML5 application to access analytic function through smartphones and other mobile devices. The dashboard’s real-time synchronization mechanisms allow the tracking of information flows within InVID’s contextualized information space. This will include the ability to display image and video content and use thumbnails to represent related stories and content clusters, thereby integrating visual content into existing Web intelligence and knowledge co-creation workflows. The result will extend the capabilities of the webLyzard platform and provide interactive data visualization widgets to be integrated into various InVID applications.
The following screenshot shows the current prototype of the dashboard based on a query on “international relations” between January and February 2017 – including a story flow visualization to reveal document clusters, a sorted list of top stories including image thumbnail and lead article, and a video playback widget in the upper right corner. The dashboard’s online documentation provides additional details on its various other visual analytics capabilities.
InVID Verification Application
The InVID Verification Application is a web-based integrated toolset for the verification of videos and their context developed by Condat AG, Berlin. Its main target are journalists who wish to verify if a given video is authentic or not. Malicious use of videos can occur in many ways, such as taking authentic videos out of their true context and putting them into another context, or creating fake videos. In order to help the journalist to evaluate the originality and trustworthiness of a user-generated video (UGV), a number of different services are integrated into the Verification Application, which are provided by the different InVID partners. These services perform: context aggregation and analysis, which includes the detection of locations, tweet mentions and the collection of further related metadata; logo detection, which identifies the existence of given logos in the videos; near duplicate search, which helps to find videos or parts of them that have already been published in the past; forensic analysis with the help of different filters that assist the journalist to decide if the video has been tampered.
Additional InVID technologies will be integrated in the near future to support the direct uploading and management of UGVs, and the management of content’s rights, while other tools for the evaluation of different dimensions of video verificaiton (such as Wolfram Alpha, links to fact checking sites, etc.) could be also added. The development of the InVID Verification Application is guided by the well-known Verification Handbook. A publicly available (though for authorized users) version of the InVID Verification Application will be released for testing purposes in the near future.
On-line service for video fragmentation and annotation
This experimental service lets you submit videos in various formats and perform visual analysis algorithms on them: shot segmentation, scene segmentation and visual concept detection. The service allows the user to submit a video for analysis by uploading a local copy of it from the user’s machine (this is preferable), or by specifying the URL of a video available on-line. The service can handle videos of mp4, webm, avi, mov, wmv, ogv, mpg, flv, and mkv format. After fetching the video file, the service decomposes the video into shots and scenes. Following, a few hundred visual concept detectors are evaluated for each video shot, thus generating shot-level concept-based annotations. After submitting a video for analysis, the user may close the browser window and be notified by e-mail when the analysis results are ready; alternatively, the user may leave the browser window open, to see how the analysis progresses. In any case, when the analysis is completed an e-mail is sent containing the unique address at which the analysis results are displayed; the display is performed with the help of an interactive user interface, which allows the exploration of the video structure (shots, scenes) and the annotations, and the concept-based search within the collection of shots. Try this service now!
Rights Management Service
The first version of the Rights Management service has been released. This service aims to assist journalists through the process of clearing the copyright of User Generated Videos (UGV) that have been indicated as relevant and useful for presenting a story, in order to enable their reuse. The service guides the journalists through recommended copyright management workflows, like the one proposed by YouTube that includes the provision of proper attribution and the contact with the content owner. If the latter is already registered in the InVID platform the communication is performed via the system, while in a different case a request for content reuse together with an invitation for registration to the InVID platform is sent by the service to the content owner. This registration can be made using social network credentials and facilitates the easier verification of the registered users as the content uploaders of their UGVs, and the effortless and timely acceptance or rejection of content reuse requests.
An online demo of this service is available at: https://rights.invid.udl.cat
The API of the service is accessible at: https://rights-api.invid.udl.cat
The documentation of this service can be found at: https://rights-api.invid.udl.cat/docs/index.html
A demo account for journalists can be provided by e-mailing to firstname.lastname@example.org
InVID Context Aggregation and Analysis tool
The InVID Context Aggregation and Analysis application (available at: http://caa.iti.gr/) aims at assisting investigators in evaluating the credibility of videos posted online. Currently applicable to YouTube videos, the service collects, analyzes and presents contextual information from YouTube, Twitter and a third party weather API to assist investigators in evaluating the video. With respect to YouTube, the tool presents in a concise format all information provided by the API, such as upload date and number of views, but also goes a step further by scanning all comments and keeping those that can play a part in verification (e.g. those claiming that the video is “fake”). It also extracts all location and date/time information from the video description, and allows the user to view a weather report for the reported date and location, so that investigators can easily compare it with the weather depicted in the video.
Furthermore, the tool searches Twitter for references to the video, and collects all relevant tweets. It presents them in an interactive timeline to allow for an overview of the Twitter traffic around the item, but also submits all tweets to the Tweet Verification Assistant service (http://reveal-mklab.iti.gr/reveal/fake/). Aggregate analytics over the submitted tweets are offered to the user, giving an overall estimate of the likelihood that the video is fake.
InVID Logo Detection tool
The InVID Logo Detection tool (accessible at: http://logos.iti.gr/) scans images and videos for logos, and provides background information on the respective organizations or groups with which they are associated. Currently, the tool has been trained to recognize a number of TV channel logos, but the logo dataset is extensible and the aim is to include more informal – and less recognizable – groups, such as paramilitary groups or independent journalistic organizations. Given an image or a YouTube video, the tool scans it and detects any logos from its index. If a match is found, the user is provided with the logo name, the keyframe and timestamp where the logo was detected – for confirmation -, and a link to the Wikipedia entry providing more information on the organization associated with the logo.