The DOI matches its Crossref record; 224 of the 224 references it cites were found in a registry or an index.
Human detection from images and videos: A survey
Open accessAbstract
The problem of human detection is to automatically locate people in an image or video sequence and has been actively researched in the past decade. This paper aims to provide a comprehensive survey on the recent development and challenges of human detection. Different from previous surveys, this survey is organised in the thread of human object descriptors. This approach has advantages in providing a thorough analysis of the state-of-the-art human detection methods and a guide to the selection of appropriate methods in practical applications. In addition, challenges such as occlusion and real-time human detection are analysed. The commonly used evaluation of human detection methods such as the datasets, tools, and performance measures are presented and future research directions are highlighted. HighlightsA review on the state-of-the-art of human detection.This review is organised in the thread of human object descriptors.Challenges such as occlusion and real-time human detection are analysed.The commonly used datasets, tools, and performance measures are presented.Open issues and future research directions are highlighted.A guide to the selection of detection methods for applications is provided.
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Cites
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Recent advances in convolutional neural networks
Gu, J., Wang, Z., Kuen, J., Ma, L., Shahroudy, A., Shuai, B., Liu, T., Wang, X., Wang, G., Cai, J., et al. (2018) · Pattern Recognition · doi:10.1016/j.patcog.2017.10.013 · Cited by 6,576
Facial Expression Analysis under Partial Occlusion: A Survey
Zhang, L., Verma, B., Tjondronegoro, D., & Chandran, V. (2019) · ACM Computing Surveys · doi:10.1145/3158369 · Cited by 1,258
Illumination-aware faster R-CNN for robust multispectral pedestrian detection
Li, C., Song, D., Tong, R., & Tang, M. (2019) · Pattern Recognition · doi:10.1016/j.patcog.2018.08.005 · Cited by 533
Survey on Emotional Body Gesture Recognition
Noroozi, F., Corneanu, C. A., Kaminska, D., Sapinski, T., Escalera, S., & Anbarjafari, G. (2021) · IEEE Transactions on Affective Computing · doi:10.1109/taffc.2018.2874986 · Cited by 455
Emotion Recognition for Human-Robot Interaction: Recent Advances and Future Perspectives
Spezialetti, M., Placidi, G., & Rossi, S. (2020) · Frontiers in Robotics and AI · doi:10.3389/frobt.2020.532279 · Cited by 293
Metadata
- Authors
- Nguyen, D. T., Li, W., & Ogunbona, P. O.
- Venue
- Pattern Recognition
- Publisher
- Elsevier BV
- Published
- 2016-03
- Volume
- 51
- Pages
- 148-175
- ISSN
- 0031-3203 (ISSN-L)
- OpenAlex
- W1833143043
- Cited by
- 267
- References
- 224
- FWCI
- 15.02
- Type
- journal article
- Language
- en
- Open access
- green
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