This page lists some of the datasets used in the development of the algorithms for STAIR.
- Object Grasping Data
This dataset contains the images of objects (real and synthetic), depthmaps (range image), and the grasp labels (i.e, where to grasp the object). Details
- 3-D Object Data
This dataset contains the images of objects, in kitchen and office environments, taken from a 3-D camera (swissranger). The labels (object class, and the point at which to grasp an object) are also given.
- Augmented dataset for Object recognition
A database of 10 office object classes, collected in a real-world cluttered environment and on green screen. This data served us in our experimental work, and also to develop classifiers for our mobile robotics application. For collecting this data, we used our technique proposed in:
A Fast Data Collection and Augmentation Procedure for Object Recognition, Benjamin Sapp, Ashutosh Saxena, and Andrew Y. Ng. AAAI, 2008. More