People Counting in Crowded Environment and Re-identification-Reference-Cited by-同舟云学术

People Counting in Crowded Environment and Re-identification

Published:2019 Issue: Volume: Page:397-425
ISSN:2191-6586
Container-title:RGB-D Image Analysis and Processing
language:
Short-container-title:

Author:

Frontoni Emanuele,Paolanti Marina,Pietrini Rocco

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-030-28603-3_18

Reference73 articles.

1. Annesley J, Orwell J, Renno J (2005) Evaluation of MPEG7 color descriptors for visual surveillance retrieval. In: 2005 IEEE international workshop on visual surveillance and performance evaluation of tracking and surveillance, pp 105–112. https://doi.org/10.1109/VSPETS.2005.1570904

2. Badrinarayanan V, Kendall A, Cipolla R (2015) Segnet: a deep convolutional encoder-decoder architecture for image segmentation. arXiv preprint arXiv:1511.00561

3. Baltieri D, Vezzani R, Cucchiara R (2013) Learning articulated body models for people re-identification. In: Proceedings of the 21st ACM international conference on multimedia, pp 557–560. ACM

4. Barbosa BI, Cristani M, Del Bue A, Bazzani L, Murino V (2012) Re-identification with RGB-D sensors. In: First international workshop on re-identification

5. Bevilacqua A, Stefano LD, Azzari P (2006) People tracking using a time-of-flight depth sensor. In: 2006 IEEE international conference on video and signal based surveillance, pp 89–89. https://doi.org/10.1109/AVSS.2006.92

Cited by 4 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Embedding AI ethics into the design and use of computer vision technology for consumer’s behaviour understanding;Computer Vision and Image Understanding;2024-11

2. Retail Robot Navigation: A Shopper Behavior-Centric Approach to Path Planning;IEEE Access;2024

3. A Deep Learning-Based System for Product Recognition in Intelligent Retail Environment;Image Analysis and Processing – ICIAP 2022;2022

4. Deep understanding of shopper behaviours and interactions using RGB-D vision;Machine Vision and Applications;2020-09-13