Neuron Linear Transformation: Modeling the Domain Shift for Crowd Counting
نویسندگان
چکیده
منابع مشابه
Counting with the Crowd
In this paper, we address the problem of selectivity estimation in a crowdsourced database. Specifically, we develop several techniques for using workers on a crowdsourcing platform like Amazon’s Mechanical Turk to estimate the fraction of items in a dataset (e.g., a collection of photos) that satisfy some property or predicate (e.g., photos of trees). We do this without explicitly iterating th...
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It is important to monitor and analyze crowd events for the sake of city safety. In an EDOF (extended depth of field) image with a crowded scene, the distribution of people is highly imbalanced. People far away from the camera look much smaller and often occlude each other heavily, while people close to the camera look larger. In such a case, it is difficult to accurately estimate the number of...
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Most crowd counting methods rely on training with labeled data to learn a mapping between image features and the number of people in the scene. However, the nature of this mapping may change as a function of the scene, camera parameters, illumination etc., limiting the ability of such supervised systems to generalize to novel conditions. Here we propose an alternative, unsupervised strategy. Th...
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Crowd counting in public places has a wide spectrum of applications especially in crowd control, public space design, and pedestrian behaviour profiling. Existing counting by regression methods, which aim to learn a direct mapping between low-level features and people count without segregation or tracking of individuals, can be categorised into either global approaches or local approaches. Glob...
متن کاملScene Invariant Crowd Counting and Crowd Occupancy Analysis
In public places, crowd size may be an indicator of congestion, delay, instability, or of abnormal events, such as a fight, riot or emergency. Crowd related information can also provide important business intelligence such as the distribution of people throughout spaces, throughput rates, and local densities. A major drawback of many crowd counting approaches is their reliance on large numbers ...
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ژورنال
عنوان ژورنال: IEEE Transactions on Neural Networks and Learning Systems
سال: 2021
ISSN: 2162-237X,2162-2388
DOI: 10.1109/tnnls.2021.3051371