The sensitivity of diffuse optical tomography （DOT） imaging exponentially decreases with the increase of photon penetration depth, which leads to a poor depth resolution for DOT. In this letter, an exponential adjus...
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The sensitivity of diffuse optical tomography （DOT） imaging exponentially decreases with the increase of photon penetration depth, which leads to a poor depth resolution for DOT. In this letter, an exponential adjustment method （EAM） based on maximum singular value of layered sensitivity is proposed. Optimal depth resolution can be achieved by compensating the reduced sensitivity in the deep medium. Simulations are performed using a semi-infinite model and the simulation results show that the EAM method can substantially improve the depth resolution of deeply embedded objects in the medium. Consequently, the image quality and the reconstruction accuracy for these objects have been largely improved.
Automatic recognition of artists is very important in acoustic music indexing, browsing, and contentbased acoustic music retrieving, but synchronously it is still a challenging errand to extract the most representativ...
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Automatic recognition of artists is very important in acoustic music indexing, browsing, and contentbased acoustic music retrieving, but synchronously it is still a challenging errand to extract the most representative and salient attributes to depict diversiform artists. In this paper, we developed a novel system to complete the reorganization of artist automatically. The proposed system can efficiently identify the artist's voice of a raw song by analyzing substantive features extracted from both pure music and singing song mixed with accompanying music. The experiments on different genres of songs illustrate that the proposed system is possible.
An algorithm to refine and clean gait silhouette noises generated by imperfect motion detection techniques is developed,and a relatively complete and high quality silhouette is *** silhouettes are sequentially refined...
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An algorithm to refine and clean gait silhouette noises generated by imperfect motion detection techniques is developed,and a relatively complete and high quality silhouette is *** silhouettes are sequentially refined in two levels according to two different probabilistic *** first level is within-sequence *** silhouette in a particular sequence is refined by an individual model trained by the gait images from current *** second level is between-sequence *** the silhouettes that need further refinement are modified by a population model trained by the gait images chosen from a certain amount of *** intention is to preserve the within-class similarity and to decrease the interaction between one class and *** experimental results indicate that the proposed algorithm is simple and quite effective,and it helps the existing recognition methods achieve a higher recognition performance.
The Euclidean Steiner minimum tree problem is a classical NP-hard combinatorial optimization *** of the intrinsic characteristic of the hard computability,this problem cannot be solved accurately by efficient algorith...
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The Euclidean Steiner minimum tree problem is a classical NP-hard combinatorial optimization *** of the intrinsic characteristic of the hard computability,this problem cannot be solved accurately by efficient algorithms up to *** to the extensive applications in real world,it is quite important to find some heuristics for *** stochastic diffusion search algorithm is a newly population-based algorithm whose operating mechanism is quite different from ordinary intelligent algorithms,so this algorithm has its own advantage in solving some optimization *** paper has carefully studied the stochastic diffusion search algorithm and designed a cellular automata stochastic diffusion search algorithm for the Euclidean Steiner minimum tree problem which has low time *** results show that the proposed algorithm can find approving results in short time even for the large scale size,while exact algorithms need to cost several hours.
Aiming at the adverse effect caused by limited detecting probability of sensors on filtering preci- sion of a nonlinear system state, a novel muhi-sensor federated unscented Kalman filtering algorithm is proposed. Fir...
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Aiming at the adverse effect caused by limited detecting probability of sensors on filtering preci- sion of a nonlinear system state, a novel muhi-sensor federated unscented Kalman filtering algorithm is proposed. Firstly, combined with the residual detection strategy, effective observations are cor- rectly identified. Secondly, according to the missing characteristic of observations and the structural feature of unscented Kalman filter, the iterative process of the single-sensor unscented Kalman filter in intermittent observations is given. The key idea is that the state estimation and its error covariance matrix are replaced by the state one-step prediction and its error covariance matrix, when the phe- nomenon of observations missing occurs. Finally, based on the realization mechanism of federated filter, a new fusion framework of state estimation from each local node is designed. And the filtering precision of system state is improved further by the effective management of observations missing and the rational utilization of redundancy and complementary information among multi-sensor observa- tions. The theory analysis and simulation results show the feasibility and effectiveness of the pro- posed algorithm.
This paper proposed a novel model-based feature representation method to characterize human walking properties for individual recognition by gait. First, a new spatial point reconstruction approach is proposed to reco...
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This paper proposed a novel model-based feature representation method to characterize human walking properties for individual recognition by gait. First, a new spatial point reconstruction approach is proposed to recover the coordinates of 3D points from 2D images by the related coordinate conversion factor (CCF). The images are captured by a monocular camera. Second, the human body is represented by a connected three-stick model. Then the parameters of the body model are recovered by the method of projective geometry using the related CCF. Finally, the gait feature composed of those parameters is defined, and it is proved by experiments that those features can partially avoid the influence of viewing angles between the optical axis of the camera and walking direction of the subject.
In this paper,we propose a novel and effective approach,namely GridNet,to hierarchically learn deep representation of 3D point *** incorporates the ability of regular holistic description and fast data processing in a...
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In this paper,we propose a novel and effective approach,namely GridNet,to hierarchically learn deep representation of 3D point *** incorporates the ability of regular holistic description and fast data processing in a single framework,which is able to abstract powerful features progressively in an efficient ***,to capture more accurate internal geometry attributes,anchors are inferred within local neighborhoods,in contrast to the fixed or the sampled ones used in existing methods,and the learned features are thus more representative and discriminative to local point *** delivers very competitive results compared with the state of the art methods in both the object classification and segmentation tasks.
In order to perform a high-quality interactive rendering of large medical data sets on a single off-the-shelf PC, a LOD selection algorithm for multi-resolution volume rendering using 3D texture mapping is presented, ...
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In order to perform a high-quality interactive rendering of large medical data sets on a single off-the-shelf PC, a LOD selection algorithm for multi-resolution volume rendering using 3D texture mapping is presented, which uses an adaptive scheme that renders the volume in a region-of-interest at a high resolution and the volume away from this region at lower resolutions. The algorithm is based on several important criteria, and rendering is done adaptively by selecting high-resolution cells close to a center of attention and low-resolution cells away from this area. In addition, our hierarchical level-of-detail representation guarantees consistent interpolation between different resolution levels. Experiments have been applied to a number of large medical data and have produced high quality images at interactive frame rates using standard PC hardware.
To address two challenging problems in infrared target tracking, target appearance changes and unpre- dictable abrupt motions, a novel particle filtering based tracking algorithm is introduced. In this method, a novel...
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To address two challenging problems in infrared target tracking, target appearance changes and unpre- dictable abrupt motions, a novel particle filtering based tracking algorithm is introduced. In this method, a novel saliency model is proposed to distinguish the salient target from background, and the eigenspace model is invoked to adapt target appearance changes. To account for the abrupt motions efficiently, a two- step sampling method is proposed to combine the two observation models. The proposed tracking method is demonstrated through two real infrared image sequences, which include the changes of luminance and size, and the drastic abrupt motions of the target.
Orientation field is one of the intrinsic charac-teristics of fingerprints, and it plays very important role in many processing phases of fingerprint recognition such as enhancement, minutiae extraction and matching. ...
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ISBN:
(纸本)9781467321969
Orientation field is one of the intrinsic charac-teristics of fingerprints, and it plays very important role in many processing phases of fingerprint recognition such as enhancement, minutiae extraction and matching. Therefore, accurate estimation of orientation filed is much necessary. In this paper, a novel PDE-based method is proposed for regularization of orientation field for low-quality fingerprint images. The method consists of four steps. Firstly, the coarse orientation field is computed using traditional gradient-based approach. Secondly, the reliability map of the orientation field is computed based on a procedure of multiscale coherence analysis. Then the orientation in the low-reliable region is reconstructed with the surrounding data by means of image inpainting technique. Finally, nonlinear diffusion filtering with adaptive diffusivity is performed on the whole orientation field. Experiments on the NIST SD4 fingerprint database indicated that the proposed algorithm is capable to estimate the orien-tation field accurately, especially for poor-quality fingerprints, and it can be integrated into fingerprint recognition systems to improve the performance.
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