Deindustrialization and the Polarization of Household Incomes: The Example of Urban Agglomerations in Germany

Goebel, Jan; Gornig, Martin

doi:10.2139/ssrn.2611607

Cited by 1 publication

(1 citation statement)

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“…Among its notable features are: it does not use intrusive methods with the user and requires an average time of 0.25 s for an instant recognition of activity [18][19][20][21][22]. It is also noted that in all the tests the recognitions were met by surpassing problems of brightness and occlusions to allow completely natural movements of the user.…”

Section: Discussionmentioning

confidence: 99%

Human Activity Recognition without Vision Tracking

Vázquez¹,

Aranda²,

Icaza³

et al. 2019

Intelligent Video Surveillance

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This work describes the recognition of human activity based on the interaction between people and objects in domestic settings, specifically in a kitchen. The difference between this and other proposals is that considers a human activity in a process without vision tracking. Videos are a sequence of photographs. Taking this into account, if you analyze an orderly sequence of images it could be based on the objects present in each scene so that you can understand the possible activity performed. However, it is not enough to consider the objects present in the scene; it is necessary to determine if those objects are employed or not by the humans present. If they are used, it is evident that they are necessary to carry out the activity; if they are not used they would only provide noise to the recognized activity. Therefore, it is necessary to generate a conceptualization of objects in the scene with characteristics (definition of an object, motion detector, object recognition, object position, object action) that allows you to recognize them and to determine the degree of use (unchanged, added, removed, moved, and indeterminate) and influence the possible recognized activity.

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Section: Discussionmentioning

confidence: 99%