ChaLearn Looking at People Challenge 2014: Dataset and Results
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The Chalearn 2014 Looking at People Challenge (track 3) dataset consists of 13,858 instances of Italian conversational gestures performed by different people and recorded with a consumer RGB-D sensor.
“The Chalearn 2014 Looking at People Challenge (track 3) dataset [14] consists of 13,858 instances of Italian conversational gestures performed by different people and recorded with a consumer RGB-D sensor.”
From ModDrop: Adaptive Multi-Modal Gesture Recognition (2016) · cites this paper as [14]
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- Authors
- Escalera, S., Baró, X., Gonzàlez, J., Bautista, M. A., Madadi, M., Reyes, M., Ponce-López, V., Escalante, H. J., Shotton, J., & Guyon, I.
- Affiliations
- Universitat Oberta de Catalunya (ES)
- Universitat Autònoma de Barcelona (ES)
- Computer Vision Center (ES)
- National Institute of Astrophysics, Optics and Electronics (MX)
- Microsoft (United States) (US)
- ChaLearn (US)
- ORCID
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer International Publishing
- Published
- 2015
- Pages
- 459-473
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W619311409
- Cited by
- 211
- References
- 18
- Citations by year
- 2026: 1 · 2025: 7 · 2024: 11 · 2023: 14 · 2022: 11 · 2021: 19 · 2020: 17 · 2019: 14 · 2018: 27 · 2017: 28 · 2016: 24 · 2015: 37 · 2014: 1
- FWCI
- 15.86
- Type
- conference paper
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Lecture notes in computer science (publishedVersion)
- HAL (submittedVersion)
- UCL Discovery (University College London) (submittedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Human Pose and Action Recognition
- Physical Sciences › Computer Science › Human-Computer Interaction › Hand Gesture Recognition Systems
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Context-Aware Activity Recognition Systems
- Keywords
- human action recognition, user-independent recognition, Jaccard similarity, benchmark dataset
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