crowd counting







Feature mining for localised crowd counting .
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This paper presents a multi-output regression model for crowd counting in public scenes. Existing counting by regression methods either learn a single model for global counting , or train a large number of separate regressors for localised density estimation. In contrast, our

3D Crowd Counting via Multi-View Fusion with 3D Gaussian Kernels
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Crowd counting has been studied for decades and a lot of works have achieved good performance, especially the DNNs-based density map estimation methods. Most existing crowd counting works focus on single-view counting , while few works have studied multi

Crowd Pedestrian Counting Considering Network Flow Constraints in Videos
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A quadratic programming method with network flow constraints is proposed to improve crowd pedestrian counting in video surveillance. Most of the existing approaches estimate the number of pedestrians within one frame, which result in inconsistent predictions in

Counting of people in the extremely dense crowd using genetic algorithm and blobs counting
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In this paper, we have proposed a framework to count the moving person in the video automatically in a very dense crowd situation. Median filter is used to segment the foreground from the background and blob analysis is done to count the people in the current

A Literature Study on Crowd (People) Counting With the Help of Surveillance Videos
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The categories of crowd counting in video falls in two broad categories:(a) ROI counting which estimates the total number of people in some regions at certain time instance (b) LOI counting which counts people who crosses a detecting line in certain time duration. The LOI

People counting in extremely dense crowd using blob size optimization
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Estimating Crowd density and counting people is an important factor in crowd management. The increase of number of people in small areas create problems like physical injury and fatalities. Hence early detection of the crowd can avoid these problems. Counting of the

Counting people in a crowd using Viola-jones Algorithm
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Counting the number of people in crowded areas such as the Masaa of Al-Masjid Al-Haram has become a necessity. This is due to the increasing number of people performing Hajj or Umrah. In this paper, we propose a crowd counting system for the Masaa using image

Towards view invariant person counting and crowd density estimation for remote vision-based services
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Crowd monitoring in mass events is a highly important technology to support the safety of event attending persons. Proposed methods are often limited to one specific viewing condition and have to be retrained or even redesigned if the viewing angle is changing

Domain Adaptation in Crowd Counting
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We consider the problem of domain adaptation in crowd counting . Given an input image of a crowd scene, our goal is to estimate the count of people in the image. Previous work in crowd counting usually assumes that training and test images are captured by the same

One-Shot Scene-Specific Crowd Counting
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We consider the problem of crowd counting in static images. Given an image, the goal is to estimate a density map of this image, where each value in the density map indicates the density level of the corresponding location in the image. In particular, we consider a novel

CountMe!-Low Cost Crowd Counting using Audio Tones
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With mobile devices becoming ubiquitous, collaborative applications have become increasingly pervasive. In these applications, there is a strong need to obtain a count of the number of mobile devices present in an area, as it closely approximates the size of the

Crowd counting and monitoring in a surveillance system
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This thesis implemented the technology solution for safe Rath Yatra in Ahmedabad by providing a web-based solution which mimics the Rath Yatra journey over the web portal. I have introduced new feature like crowd density estimation by modifying the Google Map

Crowd Counting with Stacked Pooling for Boosting Scale Invariance
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In this work, we take insight into the crowd counting problem by exploring the phenomenon of cross-scale visual similarity caused by perspective distortions. It is a quite common phenomenon in crowd scenarios, suggesting the crowd counting model to enable a good

Crowd Safety: A Real Time System For Counting People
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Man-made disasters are the outcome of lack of awareness, lack of sensitivity towards the safety measures to be taken to prevent unforeseen accidents. Large crowds always invite accidents if preventive measures are not taken with proper planning. When the number of

A Distributed Protocol for Crowd Counting in Urban Environments
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Monitoring, control, and estimation of spontaneous crowd formations in cities, eg, during open-air festivals or rush hour, are necessary actions to be taken by city administration. The most common way to implement these measures is via installation of observation cameras

Crowd Counting Mapping to Make a Decision
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Congestion typically occurs when the number of crowds exceeds the capacity of facilities. In some cases, when buildings have to be evacuated, people might be trapped in congestion and cannot escape from the building early enough which might even lead to stampedes Crowd counting is getting more and more attention. More and more collective activities, such as the Olympics Games and the World Expo, are also important to control the crowd number. In this paper, we address the problem of crowd counting in the crowded scene. Our model

An Empirical Evaluation of Cross-scene Crowd Counting Performance
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Crowd counting and density estimation are useful but also challenging tasks in many video surveillance systems, especially in cross-scene settings with dense crowds, if the target scene significantly differs from the ones used for training. This also holds for methods based

Supplementary Material: Switching Convolutional Neural Network for Crowd Counting
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Differential training on the CNN regressors R1 through R3 generates a multichotomy that minimizes the predicted count by choosing the best regressor for a given crowd scene patch. However, the trained switch is not ideal and the manifold separating the space of patches is

Crowd Counting Through Head Detection
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When large numbers of people gather at a specific place or location for a specific purpose, it is defined as Mass Gathering. It is important to understand the event variables that might affect the health of people present during such mass gatherings. Crowd density is one of the





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