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As a significant biometric technique, 3D palm print authentication is better than 2D palm print authentication in several aspects. Previous work on 3D palm print recognition has concentrated on two aspects: (1) extracting the texture and line features using the binary image of 3D palm print, (2) extracting the orientation features using the Gabor filter and competitive code. In this paper we extract,...
This paper introduces an approach to classify robot environments based on planar segments extracted from 3D data. In a preprocessing step, point data from a 3D range sensor is transformed to planar patches, i.e. raw data is transformed to a mid level geometric representation. This step allows for a robust, simple and straightforward feature extraction. The features are fed into a learning algorithm,...
This paper proposes a reliable solution to the problem of estimating the motion of a rigid object moving freely in 3D space, through the use of a passive vision system. The feature-based tracking technique builds upon the selection of a consistent set of features and their tracking on a frame-by-frame basis. A thorough investigation is conducted to determine a proper vision system setup, which results...
In this paper we propose a string-based approach to effectively represent trajectories in the 3D space. The strategy is coupled with a syntactical matching algorithm that allows evaluating the similarity of the retrieved data with pre-stored templates. The symbolic representation of the trajectory, is the core of the proposed system, which helps discriminating among different tracks using a modified...
Given a set of labeled 3D meshes acquired from stereo imaging of heads, the goal of this research is to develop a successful methodology for discriminating between individuals with 22q11.2 deletion syndrome and the general population. Although many approaches for such discrimination exist in the medical and computer vision literature, the goal is to develop methods that focus on shape-based morphological...
This paper presents a robust hand gesture analysis method using 3D depth data. Our scheme focuses on accurate hand segmentation by eliminating the negative effect of the forearm part. In the general human computer interaction (HCI) tasks, such an assumption usually holds that the depth of hand is smaller than forearm. Therefore, the precise hand region can be obtained through the fusion of the hand...
An extraction of important features in cancer cell image analysis is a key process in grading renal cell carcinoma. In this study, we applied three-dimensional (3D) texture feature extraction methods to cancer cell nuclei images and evaluated the validity of them for computerized cell nuclei grading. Individual images of 1,800 cell nuclei were extracted from 8 classes of renal cell carcinomas (RCCs)...
A rigorous investigation on the synergy of mechanical attributes to engineer tactics for measuring human activity in terms of forces, as well as to provide independency and discrimination clarity of action recognition using linear and non-linear classification methodologies from data mining and evolutionary computation, are the main objectives where this paper focuses on. Mechanical analysis is employed...
Feature selection is an important processing step in machine learning. Most used feature selection methods choose top-ranking features without considering the relationships among features. In this paper, the signification of feature selection is introduced, and the goal and evaluation criteria of feature selection are analyzed. The coalitional game theory related to the feature selection is explained...
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