CHORUS Deliverable 2.1: State of the Art on Multimedia Search Engines

Based on the information provided by European projects and national initiatives related to multimedia search as well as domains experts that participated in the CHORUS Think-thanks and workshops, this document reports on the state of the art related to multimedia content search from, a technical, and socio-economic perspective. The technical perspective includes an up to date view on content based indexing and retrieval technologies, multimedia search in the context of mobile devices and peer-to-peer networks, and an overview of current evaluation and benchmark inititiatives to measure the performance of multimedia search engines. From a socio-economic perspective we inventorize the impact and legal consequences of these technical advances and point out future directions of research

SalAd: A Multimodal Approach for Contextual Video Advertising

The explosive growth of multimedia data on Internet has created huge opportunities for online video advertising. In this paper, we propose a novel advertising technique called SalAd, which utilizes textual information, visual content and the webpage saliency, to automatically associate the most suitable companion ads with online videos. Unlike most existing approaches that only focus on selecting the most relevant ads, SalAd further considers the saliency of selected ads to reduce intentional ignorance. SalAd consists of three basic steps. Given an online video and a set of advertisements, we first roughly identify a set of relevant ads based on the textual information matching. We then carefully select a sub-set of candidates based on visual content matching. In this regard, our selected ads are contextually relevant to online video content in terms of both textual information and visual content. We finally select the most salient ad among the relevant ads as the most appropriate one. To demonstrate the effectiveness of our method, we have conducted a rigorous eye-tracking experiment on two ad-datasets. The experimental results show that our method enhances the user engagement with the ad content while maintaining users\u27 quality of video viewing experience

How to Get Away With Discrimination: The Use of Algorithms to Discriminate in the Internet Entertainment Industry

In July 2021, Ziggi Tyler posted a video on TikTok, a popular video sharing platform, where he expressed his frustration with being a Black content creator on TikTok. The video showed Ziggi typing phrases such as “Black Lives Matter” or “Black success” into his Marketplace creator bio, which the app would immediately flag as inappropriate content. However, when Ziggi replaced those words with “white supremacy” or “white success,” no inappropriateness warning appeared. Although a TikTok spokesperson responded to the video clarifying that the app had mistakenly flagged phrases without considering word order, Ziggi refused to let an algorithm absolve TikTok from blame, telling Vox that the company should have identified the system’s issues sooner

Logo recognition in videos: an automated brand analysis system

Every year companies spend a sizeable budget on marketing, a large portion of which is spent on advertisement of their product brands on TV broadcasts. These physical advertising artifacts are usually emblazoned with the companies' name, logo, and their trademark brand. Given these astronomical numbers, companies are extremely keen to verify that their brand has the level of visibility they expect for such expenditure. In other words advertisers, in particular, like to verify that their contracts with broadcasters are fulfilled as promised since the price of a commercial depends primarily on the popularity of the show it interrupts or sponsors. Such verifications are essential to major companies in order to justify advertising budgets and ensure their brands achieve the desired level of visibility. Currently, the verification of brand visibility occurs manually by human annotators who view a broadcast and annotate every appearance of a companies' trademark in the broadcast. In this thesis a novel brand logo analysis system which uses shape-based matching and scale invariant feature transform (SIFT) based matching on graphics processing unit (GPU) is proposed developed and tested. The system is described for detection and retrieval of trademark logos appearing in commercial videos. A compact representation of trademark logos and video frame content based on global (shape-based) and local (scale invariant feature transform (SIFT)) feature points is proposed. These representations can be used to robustly detect, recognize, localize, and retrieve trademarks as they appear in a variety of different commercial video types. Classification of trademarks is performed by using shaped-based matching and matching a set of SIFT feature descriptors for each trademark instance against the set of SIFT features detected in each frame of the video. Our system can automatically recognize the logos in video frames in order to summarize the logo content of the broadcast with the detected size, position and score. The output of the system can be used to summarize or check the time and duration of commercial video blocks on broadcast or on a DVD. Experimental results are provided, along with an analysis of the processed frames. Results show that our proposed technique is efficient and effectively recognizes and classifies trademark logos

Image Indexing and Retrieval

The amount of pictorial data has been growing enormously with the expansion of WWW. From the large number of images, it is very important for users to retrieve required images via an efficient and effective mechanism. To solve the image retrieval problem, many techniques have been devised addressing the requirement of different applications. Problem of the traditional methods of image indexing have led to the rise of interest in techniques for retrieving images on the basis of automatically derived features such as color, texture and shape… a technology generally referred as Content-Based Image Retrieval (CBIR). After decade of intensive research, CBIR technology is now beginning to move out of the laboratory into the marketplace. However, the technology still lacks maturity and is not yet being used in a significant scale

Trademarks and the COVID-19 Pandemic: An Empirical Analysis of Trademark Applications Including the Terms COVID, Coronavirus, Quarantine, Social Distancing, Six Feet Apart, and Shelter in Place

True to its nature as a (hopefully) once in a lifetime event, the COVID-19 pandemic has led to a tsunami of trademark applications. These include the terms “COVID,” “Coronavirus,” and other medical and pandemic-management related terms. This unprecedented number of applications has been highlighted by several commentators in general terms in the past months. This Article examines these applications in detail. Notably, the Article presents the first and most complete survey of the applications filed between the onset of the pandemic and the end of 2020, which include the following terms: “COVID,” “Coronavirus,” “Quarantine,” “Social Distancing,” “Six Feet Apart,” and “Shelter in Place.” The author chose to include four additional terms related to the pandemic besides “COVID” and “Coronavirus” to illustrate the broader effects of the pandemic on the trademark application process. The Article proceeds as follows: Section II describes the methodology used to collect and examine the relevant “COVID-19 related” applications; Section III presents the data with specific details regarding the products for which the applications have been filed, the type of filing entities, the legal basis for filing, and the date of filing throughout the relevant period—the year 2020; Section IV elaborates on the distinct legal challenges that the “COVID-19 related” applications may face in order to be registered, notably the possibility that the signs are found to be descriptive, generic, or misleading, or cannot function as marks; Section V concludes and compares the data related to these applications with previous filings for signs including terms related to past sensational events, including pandemics. This comparison shows that the numbers of “COVID-19 related” applications are much higher than the filings submitted in the past. Moreover, 2020 saw a large increase in the numbers of trademark filings including other medical terms. This again illustrates the catalyst effect of the COVID-19 pandemic on the trademark application system. For the interest of the readers, the Article includes the complete dataset presented as Appendix

Newman v. Google

3rd amended complain