Current Issue : October - December Volume : 2012 Issue Number : 4 Articles : 4 Articles
One of the most important issues in human motion analysis is the tracking and 3D reconstruction of human motion, which\r\nutilizes the anatomic points� positions. These points can uniquely define the position and orientation of all anatomical segments.\r\nIn this work, a new method is proposed for tracking and 3D reconstruction of human motion from the image sequence of a\r\nmonocular static camera. In this method, 2D tracking is used for 3D reconstruction, which a database of selected frames is used\r\nfor the correction of tracking process. The method utilizes a new image descriptor based on discrete cosine transform (DCT),\r\nwhich is employed in different stages of the algorithm. The advantage of using this descriptor is the capabilities of selecting proper\r\nfrequency regions in various tasks, which results in an efficient tracking and pose matching algorithms. The tracking and matching\r\nalgorithms are based on reference descriptor matrixes (RDMs), which are updated after each stage based on the frequency regions\r\nin DCT blocks. Finally, 3D reconstruction is performed using Taylor�s method. Experimental results show the promise of the\r\nalgorithm....
A multiresolution feature extraction algorithm for face recognition is proposed based on two-dimensional discrete wavelet transform(\r\n2D-DWT), which efficiently exploits the local spatial variations in a face image. For feature extraction, instead of considering\r\nthe entire face image, an entropy-based local band selection criterion is developed, which selects high-informative horizontal\r\nsegments from the face image. In order to capture the local spatial variations within these bands precisely, the horizontal band\r\nis segmented into several small spatial modules. The effect of modularization in terms of the entropy content of the face images\r\nhas been investigated. Dominant wavelet coefficients corresponding to each module residing inside those bands are selected as\r\nfeatures. A histogram-based threshold criterion is proposed to select dominant coefficients, which drastically reduces the feature\r\ndimension and provides high within-class compactness and high between-class separability. The effect of using different mother\r\nwavelets for the purpose of feature extraction has been also investigated. PCA is performed to further reduce the dimensionality\r\nof the feature space. Extensive experimentation is carried out upon standard face databases, and a very high degree of recognition\r\naccuracy is achieved by the proposed method in comparison to those obtained by some of the existing methods...
We propose a joint segmentation and groupwise registration method for cardiac perfusion images by using temporal information.\r\nThe nature of perfusion images makes groupwise registration especially attractive as the temporal information from the entire\r\nimage sequence can be used. Registration aims to maximize the smoothness of the intensity signal, while segmentation minimizes\r\na pixel�s dissimilarity with other pixels having the same segmentation label. The cost function is optimized in an iterative fashion\r\nusing B-splines. Tests on real patient datasets show that compared to two other methods, our method shows lower registration error\r\nand higher segmentation accuracy. This is attributed to the use of temporal information for groupwise registration and mutually\r\ncomplementary registration and segmentation information in one framework, while other methods solve the two problems\r\nseparately....
Defining spatiotemporal relations and modeling motion events are emerging issues of current research. Motion events are the\r\nsubclasses of spatiotemporal relations, where stable and unstable spatio-temporal topological relations and temporal order of\r\noccurrence of a primitive event play an important role. In this paper, we proposed a theory of spatio-temporal relations based\r\non topological and orientation perspective. This theory characterized the spatiotemporal relations into different classes according\r\nto the application domain and topological stability. This proposes a common sense reasoning and modeling motion events in\r\ndiverse application with the motion classes as primitives, which describe change in orientation and topological relations model.\r\nOrientation information is added to remove the locative symmetry of topological relations from motion events, and these events\r\nare defined as a systematic way. This will help to improve the understanding of spatial scenario in spatiotemporal applications....
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