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Mall - Crowd Estimation
许可协议: CC-BY-SA 4.0

Overview

This data set is added for convenience.

Data is provided in h5 files that contains images and labels.

Images corresponds to original frames.

Labels are density maps based on objects positions in each frame.

Density maps were scaled to 100 * number of objects to make the network learn better.

Density maps were produced by applying a convolution with a Gaussian kernel.

Order of frames is maintained and dataset is split into (1500) frames for training and (500) frames for validation.

Script used to generate this dataset can be found in this github repo: https://github.com/NeuroSYS-pl/objects_counting_dmap

Official link: https://personal.ie.cuhk.edu.hk/~ccloy/downloads_mall_dataset.html

Details
The mall dataset was collected from a publicly accessible webcam for crowd counting and profiling research.

Ground truth: Over 60,000 pedestrians were labelled in 2000 video frames. Data is annotated exhaustively by labeling the head position of every pedestrian in all frames.

Video length: 2000 frames
Frame size: 640x480
Frame rate: < 2 Hz

The dataset is intended for research purposes only and as such cannot be used commercially. Please cite the following publication(s) when this dataset is used in any academic and research reports.

References
From Semi-Supervised to Transfer Counting of Crowds
C. C. Loy, S. Gong, and T. Xiang
in Proceedings of IEEE International Conference on Computer Vision, pp. 2256-2263, 2013 (ICCV)

Cumulative Attribute Space for Age and Crowd Density Estimation
K. Chen, S. Gong, T. Xiang, and C. C. Loy
in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, pp. 2467-2474, 2013 (CVPR, Oral)

Crowd Counting and Profiling: Methodology and Evaluation
C. C. Loy, K. Chen, S. Gong, T. Xiang
in S. Ali, K. Nishino, D. Manocha, and M. Shah (Eds.), Modeling, Simulation and Visual Analysis of Crowds, Springer, vol. 11, pp. 347-382, 2013

Feature Mining for Localised Crowd Counting
K. Chen, C. C. Loy, S. Gong, and T. Xiang
British Machine Vision Conference, 2012 (BMVC)

数据概要
数据格式
image,
数据量
2.004K
文件大小
230.77MB
发布方
Feras
| 数据量 2.004K | 大小 230.77MB
Mall - Crowd Estimation
许可协议: CC-BY-SA 4.0

Overview

This data set is added for convenience.

Data is provided in h5 files that contains images and labels.

Images corresponds to original frames.

Labels are density maps based on objects positions in each frame.

Density maps were scaled to 100 * number of objects to make the network learn better.

Density maps were produced by applying a convolution with a Gaussian kernel.

Order of frames is maintained and dataset is split into (1500) frames for training and (500) frames for validation.

Script used to generate this dataset can be found in this github repo: https://github.com/NeuroSYS-pl/objects_counting_dmap

Official link: https://personal.ie.cuhk.edu.hk/~ccloy/downloads_mall_dataset.html

Details
The mall dataset was collected from a publicly accessible webcam for crowd counting and profiling research.

Ground truth: Over 60,000 pedestrians were labelled in 2000 video frames. Data is annotated exhaustively by labeling the head position of every pedestrian in all frames.

Video length: 2000 frames
Frame size: 640x480
Frame rate: < 2 Hz

The dataset is intended for research purposes only and as such cannot be used commercially. Please cite the following publication(s) when this dataset is used in any academic and research reports.

References
From Semi-Supervised to Transfer Counting of Crowds
C. C. Loy, S. Gong, and T. Xiang
in Proceedings of IEEE International Conference on Computer Vision, pp. 2256-2263, 2013 (ICCV)

Cumulative Attribute Space for Age and Crowd Density Estimation
K. Chen, S. Gong, T. Xiang, and C. C. Loy
in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, pp. 2467-2474, 2013 (CVPR, Oral)

Crowd Counting and Profiling: Methodology and Evaluation
C. C. Loy, K. Chen, S. Gong, T. Xiang
in S. Ali, K. Nishino, D. Manocha, and M. Shah (Eds.), Modeling, Simulation and Visual Analysis of Crowds, Springer, vol. 11, pp. 347-382, 2013

Feature Mining for Localised Crowd Counting
K. Chen, C. C. Loy, S. Gong, and T. Xiang
British Machine Vision Conference, 2012 (BMVC)

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