We propose a novel crowd counting approach that leverages abundantly available unlabeled crowd imagery in a learning-to-rank framework. To induce a ranking of cropped images , we use the observation that any sub-image of a crowded scene image is guaranteed to contain the same number or fewer persons than the super-image. This allows us to address the problem of limited size of existing datasets...

Crowdsourcing has gained much attention in practice over the last years. Numerous companies have drawn on this concept for performing different tasks and value creation activities. Nevertheless, despite its popularity, there is still comparatively little well-founded knowledge on crowdsourcing, particularly with regard to the governance of crowdsourcing initiatives. Although proper governance i...

Peer crowds serve as an identity marker for adolescents, indicating their image and status among peers; but adolescents do not always endorse peer appraisals of crowd affiliation. We report on two studies—one with 924 adolescents in grades 7–12 and a second with a more diverse population of 2,728 students in grades 9–11, followed for 2 years—that examined how congruence between peer and self-ap...

Many studies have been done on expert-rated crowdsourcing contests but few have examined crowd-rated contests in which winners are determined by the voting of the crowd. Due to the different rating mechanisms, determinants for winning may be different under two types of contests. Based on previous studies, we identify three types of winning determinants: expertise, submission timing, and social...

We introduce and test a crowdsourcing technique for creative problem solving. In total, 1853 workers from Amazon’s Mechanical Turk produced 468 ideas for solving the 2010 oil spill problem in the Gulf of Mexico. In our technique, one crowd generated initial ideas, another crowd evaluated the creativity of these ideas, and yet another crowd combined pairs of ideas produced by the previous crowd....

We show how the quality of decisions based on the aggregated opinions of the crowd can be conveniently studied using a sample of individual responses to a standard IQ questionnaire. We aggregated the responses to the IQ questionnaire using simple majority voting and a machine learning approach based on a probabilistic graphical model. The score for the aggregated questionnaire, Crowd IQ, serves...

The increase of population causes the raise of security threat in crowed environment, which makes crowd counting becoming more and more important. For common complexity scenes, existing crowd counting approaches are mainly based on regression models which learn a mapping between low-level features and class labels. One of the major challenges for generating a good regression function is the ins...

We propose an entropic geometrical model of psycho–physical crowd dynamics (with dissipative crowd kinematics), using Feynman action–amplitude formalism that operates on three synergetic levels: macro, meso and micro. The intent is to explain the dynamics of crowds simultaneously and consistently across these three levels, in order to characterize their geometrical properties particularly with ...