This paper presents a novel method for online and incremental appearance-based localization and mapping in a highly dynamic environment. Using position-invariant robust features (...
Online adaptation is a key requirement for image processing applications when used in dynamic environments. In contrast to batch learning, where retraining is required each time a...
This paper presents a robust object tracking method via a spatial bias appearance model learned dynamically in video. Motivated by the attention shifting among local regions of a ...
Shared sensing infrastructures that allow multiple applications to share deployed sensors are emerging and Internet protocol based access for such sensors has already been prototy...
We provide a provably efficient algorithm for learning Markov Decision Processes (MDPs) with continuous state and action spaces in the online setting. Specifically, we take a mo...