Performing 3D interactions with virtual objects easily becomes a complex task, limiting the implementation of larger applications. In order to overcome some of these limitations, ...
Abstract. We propose a framework that learns functional objectes from spatio-temporal data sets such as those abstracted from video. The data is represented as one activity graph t...
Muralikrishna Sridhar, Anthony G. Cohn, David C. H...
We present a novel approach for unsupervised discovery of repetitive objects from 3D point clouds. Our method assumes that objects are geometrically consistent, and uses multiple o...
We analyze the amount of information needed to carry out model-based recognition tasks, in the context of a probabilistic data collection model, and independently of the recogniti...
A new particle filter, Kernel Particle Filter (KPF), is proposed for visual tracking for multiple objects in image sequences. The KPF invokes kernels to form a continuous estimate...