Poselet Key-Framing: A Model for Human Activity Recognition

Project Members

Michalis Raptis (Disney Research Pittsburgh)
Leonid Sigal (Disney Research Pittsburgh)

 

 Poselet Key-framing- A Model for Human Activity Recognition-Image

In this paper, we develop a new model for recognizing human actions. An action is modeled as a very sparse sequence of temporally local discriminative keyframes – collections of partial key-poses of the actor(s), depicting key states in the action sequence. We cast the learning of keyframes in a max-margin discriminative framework, where we treat keyframes as latent variables. This allows us to (jointly) learn a set of most discriminative keyframes while also learning the local temporal context between them. Keyframes are encoded using a spatially-localizable poselet-like representation with HoG and BoW components learned from weak annotations; we rely on structured SVM formulation to align our components and mine for hard negatives to boost localization performance. This results in a model that supports spatio-temporal localization and is insensitive to dropped frames or partial observations. We show classification performance that is competitive with the state of the art on the benchmark UT-Interaction dataset and illustrate that our model outperforms prior methods in an on-line streaming setting.

Publications

Poselet Key-framing- A Model for Human Activity Recognition-Thumbnail

Poselet Key-framing: A Model for Human Activity Recognition
June 25, 2013
IEEE Conference on Computer Vision Pattern Recognition (CVPR) 2013
Paper File [pdf, 5.02 MB]

Copyright Notice

The documents contained in these directories are included by the contributing authors as a means to ensure timely dissemination of scholarly and technical work on a non-commercial basis. Copyright and all rights therein are maintained by the authors or by other copyright holders, notwithstanding that they have offered their works here electronically. It is understood that all persons copying this information will adhere to the terms and constraints invoked by each author's copyright. These works may not be reposted without the explicit permission of the copyright holder.