Poselets and Their Applications in High-Level Computer Vision

Abstract

We address the classic problems of detection and segmentation using a part based detector that operates on a novel part, which we refer to as a poselet. Poselets are tightly clustered in both appearance space (and thus are easy to detect) as well as in configuration space (and thus are helpful for localization and segmentation). We demonstrate poselets are effective for detection, pose extraction, segmentation, action/pose estimation and attribute classification. Poselet construction requires extra annotations beyond the object bounds. To train poselets we have created H3D (Humans in 3D) - a dataset of 1200+ person annotations. The annotations include the joints, the extracted 3D pose, keypoint visibility and region labels. We have also annotated the people in the training and validation sets of PASCAL VOC 2009.

Our poselet classifier achieves state-of-the-art results for the person category on PASCAL VOC 2007, 2008, 2009 and 2010 as well as on our dataset, H3D.

 

Browse Poselets

You can browse the 150 poselets for the person category.

Results

The following are results as of September 23, 2010 for the Person category of the PASCAL VOC challenges, using Comp 4.

Dataset Score
VOC 2010
48.5
VOC 2009
48.6
VOC 2008
54.1
VOC 2007
46.9

Papers

Poselets:

Applications of poselets:

Slides

Videos

Code

Below is stand-alone code that takes an image and draws bounding boxes of the people in it in C++ and in Matlab. The Matlab version can also perform interactive visualization of the poselets. Requirements: Matlab + Image Processing toolbox. The code is released with a non-commercial license. The released code and trained detector is similar to the one we used in the PASCAL 2010 competition, which is slightly improved in accuracy (but slower) than our ECCV 2010 paper. The included model was trained for PASCAL2007. The C++ port has nearly identical output and the Matlab code is adapted so it can be used with the Parallel Computing Toolbox (i.e. all globals are removed).

April 2013 release (Matlab). PASCAL 2007 AP 46.41 (47.02 with the old PASCAL measurement method)

April 2013 release (C++). PASCAL 2007 AP 46.34 (46.96 with the old PASCAL measurement method)


Note: If you use WinZip and Matlab reports that your file is corrupt, please try WinRAR. If you need an older release please let is know.

Datasets

H3D Annotation tool

The Java3D tool that we used to create H3D and a video tutorial are available here. There are no license restrictions on using the tool for your own annotations.

Contact us

For comments or questions about poselets please email Lubomir Bourdev lubomir.bourdev -at- gmail.com.