We propose a new learning method which exploits temporal consistency to successfully learn a complex appearance model from a sparsely labeled training video. Our approach consists...
Abstract. We discuss a new optimisation for recursive functions yielding multiple results in tuples for lazy functional languages, like Clean and Haskell. This optimisation improve...
In this paper, we propose a particle filtering approach for the problem of registering two point sets that differ by a rigid body transformation. Typically, registration algorithms...
Romeil Sandhu, Samuel Dambreville, Allen Tannenbau...
We present the Recursive Least Squares Dictionary Learning Algorithm, RLSDLA, which can be used for learning overcomplete dictionaries for sparse signal representation. Most Dicti...
In this paper we introduce “clipping,” a new method of syntactic approximation which is motivated by and works in conjunction with a sound and decidable denotational model for...