We present a novel approach for extracting cluttered objects based on their morphological properties1 . Specifically, we address the problem of untangling C. elegans clusters in h...
Tammy Riklin Raviv, Vebjorn Ljosa, Annie L. Conery...
In this paper we present a framework for semantic scene parsing and object recognition based on dense depth maps. Five viewindependent 3D features that vary with object class are e...
We propose a two-state Markov chain model of degraded document images. The model generates random and burst noise to simulate isolated pixel reversal as well as blurring of a larg...
In this paper, a new segmentation approach for sets of 3D unorganized points is proposed. The method is based on a clustering procedure that separates the modes of a non-parametri...
Umberto Castellani, Marco Cristani, Vittorio Murin...
Graph-cuts based algorithms are effective for a variety
of segmentation tasks in computer vision. Ongoing research
is focused toward making the algorithms even more general,
as ...