scispace - formally typeset
Search or ask a question
Topic

Crowdsourcing

About: Crowdsourcing is a research topic. Over the lifetime, 12889 publications have been published within this topic receiving 230638 citations.


Papers
More filters
Proceedings ArticleDOI
04 May 2015
TL;DR: A publicly available video dataset of typical drone-based surveillance sequences in a car parking is created and five privacy protection filters are assessed via a crowdsourcing evaluation.
Abstract: Mini-drones are increasingly used in video surveillance. Their areal mobility and ability to carry video cameras provide new perspectives in visual surveillance which can impact privacy in ways that have not been considered in a typical surveillance scenario. To better understand and analyze them, we have created a publicly available video dataset of typical drone-based surveillance sequences in a car parking. Using the sequences from this dataset, we have assessed five privacy protection filters via a crowdsourcing evaluation. We asked crowdsourcing workers several privacy- and surveillance-related questions to determine the tradeoff between intelligibility of the scene and privacy, and we present conclusions of this evaluation in this paper.

68 citations

Journal ArticleDOI
TL;DR: Wang et al. as mentioned in this paper proposed a blockchain-empowered and decentralized trusted service mechanism for the crowdsourcing system in 5G-enabled smart cities, which is divided into nine stages: initialization, task submission, task publication, task reception, scheme submission, scheme arbitration, payment, task rollback, and service compensation.

67 citations

Journal ArticleDOI
TL;DR: This paper proposes to learn the weights for weighted MV by exploiting the expertise of annotators, model the domain knowledge of different annotators with different distributions and treat the crowdsourcing problem as a domain adaptation problem.
Abstract: Crowdsourcing labeling systems provide an efficient way to generate multiple inaccurate labels for given observations. If the competence level or the “reputation,” which can be explained as the probabilities of annotating the right label, for each crowdsourcing annotators is equal and biased to annotate the right label, majority voting (MV) is the optimal decision rule for merging the multiple labels into a single reliable one. However, in practice, the competence levels of annotators employed by the crowdsourcing labeling systems are often diverse very much. In these cases, weighted MV is more preferred. The weights should be determined by the competence levels. However, since the annotators are anonymous and the ground-truth labels are usually unknown, it is hard to compute the competence levels of the annotators directly. In this paper, we propose to learn the weights for weighted MV by exploiting the expertise of annotators. Specifically, we model the domain knowledge of different annotators with different distributions and treat the crowdsourcing problem as a domain adaptation problem. The annotators provide labels to the source domains and the target domain is assumed to be associated with the ground-truth labels. The weights are obtained by matching the source domains with the target domain. Although the target-domain labels are unknown, we prove that they could be estimated under mild conditions. Both theoretical and empirical analyses verify the effectiveness of the proposed method. Large performance gains are shown for specific data sets.

67 citations

Book
04 Feb 2016
TL;DR: This book provides unified, comprehensive coverage of contest theory as developed in economics, computer science, and statistics, with a focus on online services applications, allowing professionals, researchers and students to learn about the underlying theoretical principles and to test them in practice.
Abstract: Contests are prevalent in many areas, including sports, rent seeking, patent races, innovation inducement, labor markets, scientific projects, crowdsourcing and other online services, and allocation of computer system resources. This book provides unified, comprehensive coverage of contest theory as developed in economics, computer science, and statistics, with a focus on online services applications, allowing professionals, researchers and students to learn about the underlying theoretical principles and to test them in practice. The book sets contest design in a game-theoretic framework that can be used to model a wide-range of problems and efficiency measures such as total and individual output and social welfare, and offers insight into how the structure of prizes relates to desired contest design objectives. Methods for rating the skills and ranking of players are presented, as are proportional allocation and similar allocation mechanisms, simultaneous contests, sharing utility of productive activities, sequential contests, and tournaments.

67 citations

Proceedings ArticleDOI
TL;DR: A supervised approach to automatically detect creative video is evaluated, with promising results, showing that it is necessary to model both aesthetic value and novelty to achieve optimal classification accuracy.
Abstract: The notion of creativity, as opposed to related concepts such as beauty or interestingness, has not been studied from the perspective of automatic analysis of multimedia content. Meanwhile, short online videos shared on social media platforms, or micro-videos, have arisen as a new medium for creative expression. In this paper we study creative micro-videos in an effort to understand the features that make a video creative, and to address the problem of automatic detection of creative content. Defining creative videos as those that are novel and have aesthetic value, we conduct a crowdsourcing experiment to create a dataset of over 3,800 micro-videos labelled as creative and non-creative. We propose a set of computational features that we map to the components of our definition of creativity, and conduct an analysis to determine which of these features correlate most with creative video. Finally, we evaluate a supervised approach to automatically detect creative video, with promising results, showing that it is necessary to model both aesthetic value and novelty to achieve optimal classification accuracy.

67 citations


Network Information
Related Topics (5)
Social network
42.9K papers, 1.5M citations
87% related
User interface
85.4K papers, 1.7M citations
86% related
Deep learning
79.8K papers, 2.1M citations
85% related
Cluster analysis
146.5K papers, 2.9M citations
85% related
The Internet
213.2K papers, 3.8M citations
85% related
Performance
Metrics
No. of papers in the topic in previous years
YearPapers
2023637
20221,420
2021996
20201,250
20191,341
20181,396