Depth scans acquired from different views may contain nuisances such as noise, occlusion, and varying point density. We propose a novel Signature of Geometric Centroids descriptor, supporting direct shape matching on the scans, without requiring any preprocessing such as scan denoising or converting into a mesh. First, we construct the descriptor by voxelizing the local shape within a uniquely ...

This paper presents a local 3D descriptor for surface matching dubbed SHOT. Our proposal stems from a taxonomy of existing methods which highlights two major approaches, referred to as Signatures and Histograms, inherently emphasizing descriptiveness and robustness respectively. We formulate a comprehensive proposal which encompasses a repeatable local reference frame as well as a 3D descriptor...

In this paper, we present a tracking technique utilizing a simple saliency visual descriptor. Initially, we define a visual descriptor named local similarity pattern that mimics the famous texture operator local binary patterns. The key difference is that it assigns each pixel a code based on the similarity to the neighbouring pixels. Later, we simplify this descriptor to ...

This paper presents a texture descriptor for color texture classification specially designed to be robust against changes in the illumination conditions. The descriptor combines a histogram of local binary patterns (LBPs) with a novel feature measuring the distribution of local color contrast. The proposed descriptor is invariant with respect to rotations and translations of the image plane and...

a r t i c l e i n f o a b s t r a c t Robust face recognition under uncontrolled illumination conditions is an important problem for real face recognition systems. In this paper, we introduce a novel illumination-robust local descriptor named Sparse Linear Regression Binary (SLRB) descriptor. The SLRB descriptor is a bit string by binarizing the sparse linear regression coefficients in a local ...

We present PPFNet Point Pair Feature NETwork for deeply learning a globally informed 3D local feature descriptor to find correspondences in unorganized point clouds. PPFNet learns local descriptors on pure geometry and is highly aware of the global context, an important cue in deep learning. Our 3D representation is computed as a collection of point-pair-features combined with the points and no...

In this paper, we present local image descriptor using VQ-SIFT for more effective and efficient image retrieval. Instead of SIFT's weighted orientation histograms, we apply vector quantization (VQ) histogram as an alternate representation for SIFT features. Experimental results show that SIFT features using VQ-based local descriptors can achieve better image retrieval accuracy than the conventi...

By using the wavelet transform, we develop a hierarchical planar curve descriptor that decomposes a curve into components of different scales so that the coarsest scale components carry the global approximation information while the finer scale components contain the local detailed information. We show that the wavelet descriptor has many desirable properties such as multiresolution representat...