In this paper, a Shearing Invariant Texture Descriptor (SITD) is proposed, which is a theoretically and computationally simple method based on the Rotation invariant Local Binary Pattern (Rot-LBP) descriptor. In real-world applications using flatbed scanners, such as paper texture fingerprinting, it’s common for a sheet of paper to rotate during the image acquisition process. Because the rotati...

This paper presents an effective local spatiotemporal descriptor for action recognition from depth video sequences. The unique property of our descriptor is that it takes the shape discrimination and action speed variations into account, intending to solve the problems of distinguishing different pose shapes and identifying the actions with different speeds in one goal. The entire algorithm is ...

a r t i c l e i n f o Extracting local keypoints and keypoint descriptions from images is a primary step for many computer vision and image retrieval applications. In the literature, many researchers have proposed methods for representing local texture around keypoints with varying levels of robustness to photometric and geometric transformations. Gradient-based descriptors such as the Scale In...

SIFT-like local feature descriptors are ubiquitously employed in such computer vision applications as content-based retrieval, video analysis, copy detection, object recognition, photo-tourism and 3D reconstruction. Feature descriptors can be designed to be invariant to certain classes of photometric and geometric transformations, in particular, affine and intensity scale transformations. Howev...

We present a quantitative approach to the representation, classification, and generation of families of 3D (three-dimensional) particular discrete closed curves. Any 3D continuous curve can be digitalized and represented as a 3D discrete curve. Thus, a 3D discrete curve is composed of constant orthogonal straight-line segments. In order to represent 3D discrete curves, we use the orthogonal dir...

To detect smoke regions from video clips, a novel dynamic texture descriptor is proposed with Surfacelet transform and hidden Markov tree (HTM) model. The image sequence is multi-scale decomposed by a pyramid model, and the signals are decomposed to different directions using 3D directional filter banks. Then a 3D HMT model is built for obtained coefficients from Surfacelet transform with both ...

In this paper, we propose a novel local feature, called Local Orientation Adaptive Descriptor (LOAD), to capture regional texture in an image. In LOAD, we proposed to define point description on an Adaptive Coordinate System (ACS), adopt a binary sequence descriptor to capture relationships between one point and its neighbors and use multi-scale strategy to enhance the discriminative power of t...

Human protein subcellular location prediction can provide critical knowledge for understanding a protein's function. Since significant progress has been made on digital microscopy, automated image-based protein subcellular location classification is urgently needed. In this paper, we aim to investigate more representative image features that can be effectively used for dealing with the multilab...

Feature matching is an important step for many computer vision applications. This presentation introduces the development of a new feature descriptor, called SYnthetic BAsis (SYBA), for feature point description and matching. SYBA is built on the basis of the compressed sensing theory that uses synthetic basis functions to encode or reconstruct a signal. It is a compact and efficient binary des...

A complete pipeline is presented for accurate and efficient partial 3D object retrieval based on Quick Intersection Count Change Image (QUICCI) binary local descriptors a novel indexing tree. It shown how modification to the QUICCI query descriptor makes it ideal retrieval. An structure called Dissimilarity Tree proposed which can significantly accelerate searching large space of descriptors; t...