We describe a hierarchical probabilistic model for the detection and recognition of objects in cluttered, natural scenes. The model is based on a set of parts which describe the e...
Erik B. Sudderth, Antonio B. Torralba, William T. ...
— This paper describes a model-based probabilistic framework for tracking a fleet of laboratory-scale underwater vehicles using multiple fixed cameras. We model the target moti...
In this work it is shown the representation of 3D object shape acquired from grasp exploration. Electromagnetic motion tracking sensors are used on the fingers for object contour f...
Discriminative tracking has become popular tracking methods due to their descriptive power for foreground/background separation. Among these methods, online random forest is recen...
Xinchu Shi, Xiaoqin Zhang, Yang Liu, Weiming Hu, H...
This paper describes a surveillance system that uses a network of sensors of different kind for localizing and tracking people in an office environment. The sensor network consist...
Valery A. Petrushin, Gang Wei, Omer Shakil, Damian...