Results 71 to 80 of about 322,190 (190)
Cross Domain Adaptation of Crowd Counting with Model-Agnostic Meta-Learning
Applied Sciences, 2021 Counting people in crowd scenarios is extensively conducted in drone inspections, video surveillance, and public safety applications. Today, crowd count algorithms with supervised learning have improved significantly, but with a reliance on a large ...
Xiaoyu Hou +3 more
doaj +1 more source
InformationAutomated crowd counting is a crucial aspect of surveillance, especially in the context of mass events attended by large populations. Traditional methods of manually counting the people attending an event are error-prone, necessitating the development of
Abdullah N Alhawsawi +2 more
doaj +1 more source
Multi‐level features extraction network with gating mechanism for crowd counting
IET Image Processing, 2021 Crowd counting is still a practical and challenging problem owing to scale variations and information loss. Most existing methods based on the straightforward fusion of different features from a deep neural network seem to eliminate this limitation ...
Xin Zeng +3 more
doaj +1 more source
Bayesian Model Adaptation for Crowd Counts [PDF]
2015 IEEE International Conference on Computer Vision (ICCV), 2015 The problem of transfer learning is considered in the domain of crowd counting. A solution based on Bayesian model adaptation of Gaussian processes is proposed. This is shown to produce intuitive model updates, which are tractable, and lead to an adapted model (predictive distribution) that accounts for all information in both training and adaptation ...
Bo Liu 0043, Nuno Vasconcelos
openaire +2 more sources
Multi‐level feature fusion network for crowd counting
IET Computer Vision, 2021 Crowd counting has become a noteworthy vision task due to the needs of numerous practical applications, but it remains challenging. State‐of‐the‐art methods generally estimate the density map of the crowd image with the high‐level semantic features of ...
Luyang Wang +4 more
doaj +1 more source
Measuring the accuracy of crowd counting using wi-fi probe-request-frame counting technique [PDF]
, 2016 Wi-Fi in smartphones are designed to periodically transmit probe-request-frame to determine when a known access point is within range and by capitalizing this Wi-Fi behavior, crowd counting and analysis have been done by continuous monitoring and ...
Anis Amalina
core +4 more sources
Recurrent Distillation based Crowd Counting
CoRR, 2020 In recent years, with the progress of deep learning technologies, crowd counting has been rapidly developed. In this work, we propose a simple yet effective crowd counting framework that is able to achieve the state-of-the-art performance on various crowded scenes. In particular, we first introduce a perspective-aware density map generation method that
Yue Gu, Wenxi Liu
openaire +3 more sources
Analysis of Fine-Grained Counting Methods for Masked Face Counting: A Comparative Study
IEEE AccessMasked face counting is the counting of faces at various crowd densities and discriminating between masked and unmasked faces, which is generally considered to be an object (i.e., face) detection task.
Khanh-Duy Nguyen +4 more
doaj +1 more source
, 2018 15 manually annotated point patterns selected at random from the crowd counting dataset. The total number of point patterns in the dataset is 51.
Marcos Cruz (758727) +1 more
core +1 more source
Density Estimation and Crowd Counting
CoRRThis study enhances a crowd density estimation algorithm originally designed for image-based analysis by adapting it for video-based scenarios. The proposed method integrates a denoising probabilistic model that utilizes diffusion processes to generate high-quality crowd density maps.
Balachandra Devarangadi Sunil +2 more
openaire +2 more sources