HumanEva: Synchronized video and motion capture dataset and baseline algorithm for evaluation of articulated human motion. While research on articulated human motion and pose estimation has progressed rapidly in the last few years, there has been no systematic quantitative evaluation of competing methods to establish the current state of the art. We present data obtained using a hardware system that is able to capture synchronized video and ground-truth 3D motion. The resulting HumanEva datasets contain multiple subjects performing a set of predefined actions with a number of repetitions. On the order of 40,000 frames of synchronized motion capture and multi-view video (resulting in over one quarter million image frames in total) were collected at 60 Hz with an additional 37,000 time instants of pure motion capture data. A standard set of error measures is defined for evaluating both 2D and 3D pose estimation and tracking algorithms. We also describe a baseline algorithm for 3D articulated tracking that uses a relatively standard Bayesian framework with optimization in the form of Sequential Importance Resampling and Annealed Particle Filtering. In the context of this baseline algorithm we explore a variety of likelihood functions, prior models of human motion and the effects of algorithm parameters. Our experiments suggest that image observation models and motion priors play important roles in performance, and that in a multi-view laboratory environment, where initialization is available, Bayesian filtering tends to perform well. The datasets and the software are made available to the research community. This infrastructure will support the development of new articulated motion and pose estimation algorithms, will provide a baseline for the evaluation and comparison of new methods, and will help establish the current state of the art in human pose estimation and tracking.

References in zbMATH (referenced in 23 articles )

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  1. Escalera, Sergio; Athitsos, Vassilis; Guyon, Isabelle: Challenges in multimodal gesture recognition (2016) ioport
  2. Huang, Chun-Hao; Cagniart, Cedric; Boyer, Edmond; Ilic, Slobodan: A Bayesian approach to multi-view 4D modeling (2016)
  3. Elhoseiny, Mohamed; Elgammal, Ahmed: Generalized twin Gaussian processes using Sharma-Mittal divergence (2015)
  4. Gonzales, Christophe; Dubuisson, Séverine: Combinatorial resampling particle filter: an effective and efficient method for articulated object tracking (2015)
  5. Li, Wanyi; Sun, Jifeng: Human motion estimation based on low dimensional space incremental learning (2015)
  6. Eslami, S. M. Ali; Heess, Nicolas; Williams, Christopher K. I.; Winn, John: The shape Boltzmann machine: a strong model of object shape (2014)
  7. Gonczarek, Adam; Tomczak, Jakub M.: Manifold regularized particle filter for articulated human motion tracking (2014)
  8. Ma, Zhigang; Yang, Yi; Nie, Feiping; Sebe, Nicu; Yan, Shuicheng; Hauptmann, Alexander G.: Harnessing lab knowledge for real-world action recognition (2014)
  9. Ren, Carl Yuheng; Prisacariu, Victor; Reid, Ian: Regressing local to global shape properties for online segmentation and tracking (2014) ioport
  10. Yamada, Makoto; Sigal, Leonid; Chang, Yi: Domain adaptation for structured regression (2014)
  11. Ellis, Chris; Masood, Syed Zain; Tappen, Marshall F.; Laviola, Joseph J. jun.; Sukthankar, Rahul: Exploring the trade-off between accuracy and observational latency in action recognition (2013) ioport
  12. Li, Yi; Sun, Zhengxing: Articulated human motion tracking using sequential immune genetic algorithm (2013) ioport
  13. Sedai, S.; Bennamoun, M.; Huynh, D. Q.: Discriminative fusion of shape and appearance features for human pose estimation (2013) ioport
  14. Shen, Jianfeng; Yang, Wenming; Liao, Qingmin: Part template: 3D representation for multiview human pose estimation (2013) ioport
  15. Zhang, Dianyong; Miao, Zhenjiang; Chen, Shengyong; Wan, Lili: Optimization and soft constraints for human shape and pose estimation based on a 3D morphable model (2013) ioport
  16. Han, Hong; Tong, Minglei; Chen, Zhichao; Fan, Youjian: Variable structure multiple model for articulated human motion tracking from monocular video sequences (2012) ioport
  17. Hofmann, M.; Gavrila, D. M.: Multi-view 3D human pose estimation in complex environment (2012) ioport
  18. Rogez, Grégory; Rihan, Jonathan; Orrite-Uruñuela, Carlos; Torr, Philip H. S.: Fast human pose detection using randomized hierarchical cascades of rejectors (2012) ioport
  19. Schwarz, Loren Arthur; Mateus, Diana; Navab, Nassir: Recognizing multiple human activities and tracking full-body pose in unconstrained environments (2012) ioport
  20. Sigal, Leonid; Isard, Michael; Haussecker, Horst; Black, Michael J.: Loose-limbed people: estimating 3D human pose and motion using non-parametric belief propagation (2012)

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