We investigate pointing at graphical targets of arbitrary shapes. We first describe a previously proposed probabilistic Fitts' law model [7] which, unlike previous models tha...
Abstract--Object tracking systems require accurate segmentation of the objects from the background for effective tracking. Motion segmentation or optical flow can be used to segmen...
Inference is a key component in learning probabilistic models from partially observable data. When learning temporal models, each of the many inference phases requires a complete ...
We introduce a new approach, called Relative Start and Idle Time (RSIT), to solve probabilistic scheduling problems of construction repetitive projects. RSIT is a process of deter...
Chachrist Srisuwanrat, Photios G. Ioannou, Omer Ts...
Significant appearance changes of objects under different orientations could cause loss of tracking, "drifting." In this paper, we present a collaborative tracking framew...