Poselets: Body part detectors trained using 3D human pose annotations
University of California, Berkeley · Adobe Systems (United States)
Abstract
We address the classic problems of detection, segmentation and pose estimation of people in images with a novel definition of a part, a poselet. We postulate two criteria (1) It should be easy to find a poselet given an input image (2) it should be easy to localize the 3D configuration of the person conditioned on the detection of a poselet. To permit this we have built a new dataset, H3D, of annotations of humans in 2D photographs with 3D joint information, inferred using anthropometric constraints. This enables us to implement a data-driven search procedure for finding poselets that are tightly clustered in both 3D joint configuration space as well as 2D image appearance. The algorithm discovers poselets…
Citation impact
- FWCI
- 47.90
- Percentile
- 100%
- References
- 26
Authors
2Topics & keywords
- Computer science
- Artificial intelligence
- Pascal (unit)
- Detector
- Segmentation
- Pattern recognition (psychology)
- Computer vision
- Support vector machine