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In this paper, we present, first, a new method for color feature extraction based on SURF detectors. Then, we proved its efficiency for flower image classification. Therefore, we described visual content of the flower images using compact and accurate descriptors. These features are combined and the learning process is performed using a multiple kernel framework with a SVM classifier. The proposed...
Trajectories extracted by previous methods for human action recognition contain irrelevant changes, and the Orientation-Magnitude descriptors of their shapes lack the robustness to camera motion. To solve these problems, action recognition by tracking salient relative motion points is proposed in this paper. Firstly, motion boundary detector which suppresses the camera constant motion is utilized...
Non-rigid 3D shape retrieval is an active and important research topic in content based object retrieval. This problem is often cast in terms of the shapes intrinsic geometry due to its invariance to a wide range of non-rigid deformations. In this paper, we devise a novel generative model for shape retrieval based on the spectral representation of the Laplacian of a mesh. Contrary to common use, our...
Recently, convolutional neural networks (ConvNets) have achieved marvellous results in different field of recognition, especially in computer vision. In this paper, a seven-layer ConvNet using data augmentation is proposed for leaves recognition. First, we implement multiform transformations (e.g., rotation and translation etc.) to enlarge the dataset without changing their labels. This novel technique...
PET reconstruction results in images with correlations between neighbouring image voxels. Alternative reconstruction algorithms, such as OSEM reconstruction incorporating resolution modelling (RM) can significantly alter this voxel covariance. While RM has been demonstrated to reduce voxel variance, it has been suggested that the increased covariance results in increased region-based ensemble variance...
Now, gait recognition for identification has received more and more attention from biometrics researchers. Gait Energy Image(GEI) is an efficient represent method and Gabor wavelet has many excellent property, so we use the Gabor wavelet to extract the amplitude and phase feature of GEI, research their recognition ability respectively, at last, fusion the two features in rank level to gait recognition...
When tracking an extended object, traditional approaches exploit information only from measurements that are assumed to stem from the target, and discard observations assumed to have been generated elsewhere. However, the fact that these observations were received contains valuable information about where the target is not. This information, which is usually treated as clutter with little value, can...
In question answering system, the process of classifying a question to appropriate class and identification of the focus word play key role in determining accurate answer. In this paper, we propose an integrated pattern matching and machine learning approach for higher education domain that focuses on factoid question answering. We have developed a question taxonomy for higher education domain and...
A noise suppressing filter design technique to reduce deconvolution error of both-directions downward sloped asymmetrical long-tail distribution of the Random Telegraph Noise (RTN) is proposed. The filter is used in Lucy-Richardson-deconvolution (LRDec) iteration process. The deconvolution is required for inversely analyzing RTN long tail distribution effects on VLSI time-dependent operating margin...
In this paper, we present an approach for multicamera pedestrian detection exploiting the concepts of multiview geometry and the shapes of 3D geometric primitives. Multicamera occupancy maps provide peak responses corresponding to the object detection but suffer from several false detections known as ghosts. The novelty of this paper is the introduction of shape patterns which can model the objects,...
The square and rectangular shape of the pixels in the digital images for sensing and display purposes introduces several inaccuracies in the representation of digital images. The major disadvantage of square pixel shapes is the inability to accurately capture and display the details in the objects having variable orientations to edges, shapes and regions. This effect can be observed by the inaccurate...
A novel fuzzy clustering algorithm is presented in this paper, which removes the constraints generally imposed to the cluster shape when a given model is adopted for membership functions. An on-line, sequential procedure is proposed where the cluster determination is performed by using suited membership functions based on geometrically unconstrained kernels and a point-to-shape distance evaluation...
Recently it has been shown that using appropriate sampling kernel, finite rate of innovation signals can be perfectly recon structed even tough they are non-bandlimited. In the presence of noise, reconstruction is achieved by an estimation procedure of all the parameters of the incoming signal. In this paper we consider the estimation of a finite stream of pulses using the Sum of Sincs (SoS) kernel...
The semi-empirical kernel-driven Bidirectional Reflectance Distribution Function (BRDF) models have been widely used in many remotely sensed BRDF/albedo products such as MODIS products for their simplicity and physical interpretation[1]. Based on anisotropic flat index (AFX) derived from the model[2], magnitude inversion algorithm which takes BRDF archetypes as prior knowledge have been proposed[3]...
Classical unmixing algorithms focus primarily on scenarios with a single mixture. These techniques are easily extensible in the case of images with multiple discrete mixtures (i.e. no shared endmembers). Unmixing in scenarios with multiple mixtures with shared or common endmembers is significantly harder. Manifold clustering and embedding seem tailor-made for such a scenario, but generally these algorithms...
Temporal sequences of images called Satellite Image Time Series (SITS) afford a large amount of information compared to individual images in the context of temporal behavior of land cover components. Besides, graph represents a powerful tool for modeling such structured data. It offers the possibility to model the spatio-temporal relationship in a simple way for further analysis. In this paper, an...
In this paper, we address the problem of human pose estimation through a novel articulated Gaussian kernel correlation function which is applied to human pose tracking from a single depth sensor. We first derive a unified Gaussian kernel correlation that can generalize the previous Sum-of-Gaussians (SoG)-based methods for the similarity measure between a template and the observation. Furthermore,...
This paper proposes a superpixel tracking method via a graph-based hybrid discriminative-generative appearance model. By utilizing a superpixel-based graph structure as the visual representation, spatial information between superpixels is considered. For constructing the discriminative appearance model, we propose a graph-based semi-supervised support vector machine (SVM) approach by taking superpixels...
We present a computational approach for predicting the popularity score of sneakers through the analysis of growing amount of online data. Sneakers are described in several aspects based on which a popularity prediction model is constructed. In particular, we utilize the multiple kernel learning technique with customized kernels to analyze multimodal data extracted from an online sneaker magazine...
Spatial pyramid (SP) representation is an extension of bag-of-feature model which embeds spatial layout information of local features by pooling feature codes over pre-defined spatial shapes. However, the uniform style of spatial pooling shapes used in standard SP is an ad-hoc manner without theoretical motivation, thus lacking the generalization power to adapt to different distribution of geometric...
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