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In this paper, we propose a computational framework for integrating the physics of motion with the neurobiological basis of perception in order to model and recognize human actions and object activities. The essence, or gist, of an action is intrinsically related to the motion of the scene's objects. We define the Hamiltonian energy signature (HES) and derive the S-Metric to yield a global representation...
Questionnaire is often used to investigate the respondent' s opinion toward some product or service. To realize the knowledge mining from response data of questionnaire, this paper proposes one kind of visualization technique based on frequency analysis together with co-occurrence analysis. In created visualization graph, the nodes express the result of frequency analysis and the links between nodes...
Some types of biometric patterns can be represented as a collection of variable-length interconnected lines. This is the case of handwriting signature strokes, palmprint lines or infrared hand vein data. Typical variations in size, shape and orientation of these patterns for the same person make difficult to develop reliable biometric verification systems for them. Fuzzy snakes have been successfully...
Gene mention tagging is a critical step for biomedical text mining. Only when gene and gene product mentions are correctly identified could other more complex tasks, such as, gene normalization and gene-gene interaction extraction, be performed effectively. In this paper, six divergent models are implemented with different machine learning algorithms and dissimilar feature sets. We integrate these...
Object tracking is important for video analysis applications. However, tracking through occlusions is a difficult task due to significant appearance changes of the objects. Approaches based on either global features or one kind of local features can not solve the problem completely. In this paper, a multi-cue based tracking approach is introduced. It combines a corner tracking with a color and a shape...
We present a novel algorithm to segment a 3D surface mesh into visually meaningful regions. Our approach is based on an analysis of the local geometry of vertices. In particular, we begin with a novel characterization of vertices as convex, concave or hyperbolic based upon their discrete local geometry. Hyperbolic and concave vertices are considered potential feature region boundaries. We propose...
Vertex normal in triangular meshes is an essential surface attribute for point-based smoothing, mesh simplification and feature detection in fields as machine vision, virtual reality and reverse engineering. In order to investigate how weights of the algorithms for vertex normal estimation influence the vertex normal accuracy, theoretically analyses and experiments for algorithms by comparison are...
Statistical shape model (SSM) is to model the shape variation of an object. The statistical shape models are constructed by analysis of the positions of a set of landmark points based and use the surface information. In this paper, we propose a new PCA based statistical shape modeling technique and its application to medical applications. In the proposed method, boundary points of each slice are used...
A novel 3D model segmentation and retrieval method was introduced in this paper that is based on the topological information and partial geometry features of 3D mode. The proposed algorithm extracts feature for every triangular piece using flatness of a triangular, and partitions the 3D model into a set of triangular pieces with different flatness. Then, a watershed-based algorithm is developed and...
The product identity is an important topic in modern design. However very little research on the cognition of product identity based on consumers' image and design model has been reported. This article has proposed the cognition concept of the product identity image, and analyzed the main method based on the image cognition. According to the features of the product identity, this study has employed...
In general, car body parts are very complex models by thousands of differential geometrically operations. For the computer-aided car-body part automatic modeling system, this complexity is a big challenge. This paper proposes a new body-based modeling method, using body-based features and a "sculpturing" strategy to create complex model via a computer car-body parts design system. This method...
With the development of computer techniques, 3D model has been used more and more widely and content-based 3D model retrieval has been a hotspot in the area of multimedia information retrieval. How to extract 3D models' feature effectively is still a difficulty. Projection based 3D model feature extraction is an important kind in feature extraction, because of its robustness against noise, simplification...
As the key problem of content-based three-dimensional model retrieval, feature extraction methods do not achieve ideal performance at present. Most of past feature extraction methods just utilize the attributes of the model itself. Therefore, it is a promising direction to utilize the categorization information in the process of feature extraction. According to the fact that models in the same category...
The importance of 2D geometrical figures recognition in virtual reality and computational vision was a long motivation for researchers. In this paper the figures recognition using a mobile agents technology is presented. The 2D figures are represented with a graphical user interface implemented in Java. The mobile agents are used to extract information about geometrical figures drawn in the graphical...
This paper present a new method to extract shapes in drop caps and particularly the most important shape: letter itself. This method relies on a combination of a Aujol and Chambolle algorithm first, and a segmentation using a Zipf law in a second step. This method can be enhanced as a three-step process: 1) decomposition in layers 2) segmentation using a Zipf law 3) selection of connected components...
Accurately identifying corresponded landmarks from a population of shape instances is the major challenge in constructing statistical shape models. In general, shape-correspondence methods can be grouped into one of two categories: global methods and pair-wise methods. In this paper, we develop a new method that attempts to address the limitations of both the global and pair-wise methods. In particular,...
Most state-of-the-art nonrigid shape recovery methods usually use explicit deformable mesh models to regularize surface deformation and constrain the search space. These triangulated mesh models heavily relying on the quadratic regularization term are difficult to accurately capture large deformations, such as severe bending. In this paper, we propose a novel Gaussian process regression approach to...
Aiming at the problem in facial feature location, the Active Shape Models algorithm has no evaluable criterion to judge its convergence, and tend to run into local minimum when using the fixed search scale, and how to choose the scale is always an issue. This paper presents a method based on the whole shape gray grads to evaluate the search effects, and an improved search policy of multiscale. The...
The initial effort to develop a systematic approach for estimating partial similarity measure of 2D boundary curve is proposed. First the curves are segmented and a high-level structure, feature', is introduced to organize the segments into meaningful regions. Then a two-step similarity assessment approach is devised. The first step is structure similar comparison based on the structure description...
In this work, 3-D representation of human faces is obtained in a computer using a DLP projection device and a high resolution camera. Calibration of the system is carried out automatically using an image frame that is taken employing a calibration pattern. Depth information is obtained utilizing color patterns that have been used widely in recent times instead of a gray-scale pattern. Experimental...
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