人群计数相关研究 - 木易123 - 博客园
2021年3月1日 · 《Fast crowd density estimation with convolutional neural networks》2015是第一篇引入CNN的人群计数论文，使用两个级联conv-net完成， 《Deep people counting in extremely dense crowds》2015基于AlexNet实现一个深层的人群计数网络，使用的技巧包括将原图裁剪、翻转生成大量小的patches，而不 ...
A literature review of dense crowd simulation - ScienceDirect
2024年7月1日 · Dense crowd simulations pose numerous challenges that must be addressed to model pedestrian behavior in crowded environments accurately. One crucial concern is whether operational level models, which have been demonstrated to simulate realistically pedestrian phenomena and behavior in low-density situations, can maintain their applicability in ...
Dense Crowd Counting Algorithm Based on Coordinate Attention …
Abstract: Aiming at the problem of high density crowd with complex background and poor crowd density estimation ability, a dense crowd counting algorithm based on coordinate attention mechanism and inverse distance mapping is proposed. Firstly, the coordinate attention high-precision network CA-HRNet is created to obtain the head and position ...
CrowdNet | Proceedings of the 24th ACM international conference …
2016年10月1日 · As an effective way for crowd monitoring, control and behavior understanding, crowd density estimation is an important research topic in artificial intelligence applications. In this paper, we propose a new crowd density estimation method by deep ...
[2103.13516] Tracking Pedestrian Heads in Dense Crowd
2021年3月24日 · Increasing crowd density challenges visibility of humans, limiting the scalability of existing pedestrian trackers to higher crowd densities. For that reason, we propose to revitalize head tracking with Crowd of Heads Dataset (CroHD), consisting of 9 sequences of 11,463 frames with over 2,276,838 heads and 5,230 tracks annotated in diverse scenes.
Multi-source Multi-scale Counting in Extremely Dense Crowd …
Abstract: We propose to leverage multiple sources of information to compute an estimate of the number of individuals present in an extremely dense crowd visible in a single image. Due to problems including perspective, occlusion, clutter, and few pixels per person, counting by human detection in such images is almost impossible.
Hydrodynamics-Informed Neural Network for Simulating Dense Crowd …
2024年10月28日 · With global occurrences of crowd crushes and stampedes, dense crowd simulation has been drawing great attention. In this research, our goal is to simulate dense crowd motions under six classic motion patterns, more specifically, to generate subsequent motions of dense crowds from the given initial states.
CrowdNet: A Deep Convolutional Network for Dense Crowd …
2016年8月22日 · Our work proposes a novel deep learning framework for estimating crowd density from static images of highly dense crowds. We use a combination of deep and shallow, fully convolutional networks to predict the density map for a given crowd image.
Aggregate dynamics for dense crowd simulation
2009年12月1日 · Large dense crowds show aggregate behavior with reduced individual freedom of movement. We present a novel, scalable approach for simulating such crowds, using a dual representation both as discrete agents and as a single continuous system.
Machine Learning for Dense Crowd Direction Prediction Using …
Depending on the success of Recurrent Neural Network (RNN) handling of sequential data, we propose a model that is based on Long Short Term Memory (LSTM) to predict individual agents’ next locations. Our proposed approach will be tested two different densities of crowds, structured crowds, and unstructured crowds.