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Action recognition is a challenging task due to intra-class motion variation caused by diverse style and duration in performed action videos. Previous works on action recognition task are more focused on hand-crafted features, treat different sources of information independently, and simply combine them before classification. In this paper we study action recognition from depth sequences captured...
A method is presented for authenticating people on the basis of lip movement. It uses the kernel mutual subspace (KMS) method using fusion of canonical angles by kernel Fisher discriminant analysis. Its authentication accuracy is better than that of previously proposed lip-movement authentication methods when the distribution of lip images has a nonlinear structure. The similarity of KMS is canonical...
This paper presents a new approach of Reeb graph extraction adapted to 3D dynamic triangular Meshes. Particularly, we propose a new continuous scalar function, used for Reeb graph construction. This function is based on the heat diffusion properties. The restriction of the heat kernel to temporal domain makes the scalar function intrinsic and stable against perturbations. Due to the presence of neighborhood...
Use of digital image analysis for the identification of seeds has not been recognized as a validated method. Image analysis for seed identification has been previously studied, and good recognition rates have been achieved. However, the data sets used in these experiments either contain very few groups of non-verified specimens or little representation of intra-species variations. This study considered...
Indirect immunofluorescence imaging is employed as a standard method to detect antinuclear antibodies in HEp-2 cells which is important for diagnosing autoimmune diseases and other important pathological conditions involving the immune system. HEp-2 cells are generally categorised into six groups: homogeneous, fine speckled, coarse speckled, nucleolar, cytoplasmic, and centromere cells, which give...
This paper proposes a novel approach to recognize object categories in point clouds. By quantizing 3D SURF local descriptors, computed on partial 3D shapes extracted from the point clouds, a vocabulary of 3D visual words is generated. Using this codebook, we build a Bag-of-Words representation in 3D, which is used in conjunction with a SVM classification machinery. We also introduce the 3D Spatial...
This paper presents a methodology for shape recognition that focuses on dealing with the difficult problem of large deformations. The proposed methodology consists in a novel feature extraction technique, which uses a non-rigid representation adaptable to the shape. This technique employs a deformable grid based on the computation of geometrical centroids that follows a region partitioning algorithm...
Consumer depth cameras, such as the Microsoft Kinect, are capable of providing frames of dense depth values at real time. One fundamental question in utilizing depth cameras is how to best extract features from depth frames. Motivated by local descriptors on images, in particular kernel descriptors, we develop a set of kernel features on depth images that model size, 3D shape, and depth edges in a...
The paper presents three novel features for handwritten data based identity recognition. A novel framework for combining the features for identification is presented. The framework combines the features in kernel space in MKL based framework. The application of features individually and in combination is presented for writer recognition and signature verification. The writer recognition results have...
The performance of an object recognition system depends on both object representation and classification algorithms. On the one hand, Object representation by using local descriptors have become a very powerful representation of images. On the other hand, SVM has shown impressive learning and recognition performances. In this paper, we present a method for fast pedestrian classification by combining...
We propose a new high speed line tracing algorithm based on a well known differential geometric line extraction algorithm. The previously separate steps of line detection and line tracing are performed simultaneously. This allows the exclusion of non-candidates from processing. Exploiting the inherent continuity of lines and using extracted line characteristics in subsequent detection/tracing also...
The main objective of this research is to develop an image matching prototype that can retrieve images based on the geometry feature representation of a complete object or a partial object. Consequently, a shape decomposition method is introduced to preserve the shape feature for the remaining portion of a partial object and to simplify the shape complexity by breaking down into segments.
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