About Me ...
I am a Senior Research Scientist at Disney Research Pittsburgh and an Adjunct Faculty member at Carnegie Mellon University. My research focuses on articulated motion capture, motion modeling, action recognition, motion perception, manifold learning, transfer learning, character and cloth animation and a number of other directions on the fringe of computer vision, machine learning, and computer graphics. Before coming to Disney Research and CMU, I spent 2 years working as a Postdoctoral Fellow in the Department of Computer Science at University of Toronto (UofT).
- We are organizing a 1st Workshop on Storytelling with Images and Videos (VisStory).
- I will serve as an area chair for ECCV 2014.
- We have one paper accepted to NIPS 2013: Action is in the Eye of the Beholder: Eye-gaze Driven Model for Spatio-Temporal Action Localization, N. Shapovalova, M. Raptis, L. Sigal, G. Mori.
- We have one paper accepted to ICCV 2013: From Subcategories to Visual Composites: A Multi-Level Framework for Object Detection, T. Lan, M. Raptis, L. Sigal, G. Mori.
- Our ACM SIGGRAPH paper was featured in a press article.
- Our paper won a best paper award at AMDO 2012. Congratulation Mykhaylo Andriluka!
- Our last years ACM SIGGRAPH paper has been featured by Inside Science Television.
- Co-edited book Visual Analysis of Humans: Looking at People (T. Moeslund, A. Hilton, V. Krüger, L. Sigal, Eds.), ISBN 978-0-85729-996-3, Springer, 2011.
Family Member Identification from Photo Collections,
Q. Dai, P. Carr, L. Sigal, D. Hoiem,
IEEE Winter Conference on Applications of Computer Vision (WACV), 2015.
A Unified Semantic Embedding: Relating Taxonomies and Attributes,
S.-J. Hwang, L. Sigal,
Neural Information Processing Systems (NIPS), 2014.
Parameterizing Object Detectors in the Continuous Pose Space,
K. He, L. Sigal, S. Sclaroff,
European Conference on Computer Vision (ECCV), 2014.
Nonparametric Clustering with Distance Dependent Hierarchies,
S. Ghosh, M. Raptis, L. Sigal, E. Sudderth,
Conference on Uncertainty in Artificial Intelligence (UAI), 2014.
Joint Summarization of Large-scale Collections of Web Images and Videos for Storyline Reconstruction,
G. Kim, L. Sigal, E. P. Xing,
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2014.
Action is in the Eye of the Beholder: Eye-gaze Driven Model for Spatio-Temporal Action Localization,
N. Shapovalova, M. Raptis, L. Sigal, G. Mori,
Neural Information Processing Systems (NIPS), 2013.
From Subcategories to Visual Composites: A Multi-Level Framework for Object Detection,
T. Lan, M. Raptis, L. Sigal, G. Mori,
IEEE International Conference on Computer Vision (ICCV), 2013.
Poselet Key-framing: A Model for Human Activity Recognition,
M. Raptis, L. Sigal,
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2013.
Video-based 3D Motion Capture through Biped Control,
M. Vondrak, L. Sigal, J. K. Hodgins and Odest Jenkins,
ACM Transactions on Graphics (Proc. SIGGRAPH), 2012.
- Facial Expression Transfer with Input-Output Temporal Restricted Boltzmann Machines, M. Zeiler, G. Taylor, L. Sigal, I. Matthews and R. Fergus. NIPS, 2011.
- Motion Capture from Body-Mounted Cameras, T. Shiratori, H. S. Park, L. Sigal, Y. Sheikh and J. K. Hodgins. ACM SIGGRAPH, 2011.
- Human Attributes from 3D Pose Tracking, L. Sigal, D. Fleet, N. Troje, M. Livne. ECCV, 2010.
- Stable Spaces for Real-time Clothing, E. de Aguiar, L. Sigal, A. Treuille and J. K. Hodgins. ACM SIGGRAPH, 2010.
- Dynamical Binary Latent Variable Models for 3D Human Pose Tracking, G. Taylor, L. Sigal, D. Fleet and G. Hinton. CVPR, 2010.
- Estimating Contact Dynamics, M. Brubaker, L. Sigal and D. Fleet. ICCV, 2009.
- Shared Kernel Information Embedding for Discriminative Inference, L. Sigal, R. Memisevic, D. Fleet. CVPR, 2009.
- Physical Simulation for Probabilistic Motion Tracking, M. Vondrak, L. Sigal and O. C. Jenkins. CVPR, 2008.
- Combined discriminative and generative articulated pose and non-rigid shape estimation. L. Sigal, A. Balan and M.J. Black. NIPS, 2007.
- Predicting 3D People from 2D Pictures. L. Sigal and M. J. Black. AMDO, 2006. (best paper award)
- Measure Locally, Reason Globally: Occlusion-sensitive Articulated Pose Estimation. L. Sigal and M. J. Black. CVPR, 2006.
- Tracking Loose-limbed People. L. Sigal, S. Bhatia, S. Roth, M. J. Black and M. Isard. CVPR, 2004.