… representation and then finding these features in the voxel space. However, transforming a
3D mesh model into its volumetric representation is a … features from the mesh representation …

… Therefore, we consider to use RIM features to densely describe overlapping blocks, which
are … Due to these facts, our feature has a very strong discriminative ability for rotated objects, …

… be viewed as regularisers that prevent overfitting when optimising our objective function. …
of the objective function [6]. Hence, by substituting the gradient ∇f(A) of our objective function …

… Every object representation has its … used object representation. It is strongly based in
different mathematical areas, like statistics, geometry, differential calculus, mathematical analysis …

… , slow feature analysis (SFA), a novel machine learning approach proposed by Wiskott and
Sejnowski,12 has been exploited to learn temporally correlated representations for process …

… object recognition model based on incremental feature representation and a hierarchical
feature … The incremental feature representation method applies adaptive prototype generation …

… the modelling of features in machine vision. Feature representation and the feature recognition
… representation in both photogrammetry and remote sensing are presented in Section 4. …

… This section will discuss more about the advantages of the HGPP object representation. …
As a kind of histogram-based object representation method, HGPP cannot be matched directly …

… the identification of planar objects based on a projectively invariant representation of
shape. … or object pose computation, and the use of index functions. We describe the feature …

… neural-representation candidates. In order to attain this objective, I present first the results
of a survey of authors within two domains, place-cell and multivariate pattern analysis (MVPA) …