Titlebook: Advances in Visual Computing; 4th International Sy George Bebis,Richard Boyle,Laura Monroe Conference proceedings 2008 Springer-Verlag Berl

Pseudoephedrine

Classification of Multispectral High-Resolution Satellite Imagery Using LIDAR Elevation Datahis, multispectral and LIDAR elevation data are integrated in a single imagery file composed of independent multiple bands. The Support Vector Machine is used to classify the imagery. A scheme of five classes was chosen; ground truth samples were then collected in two sets, one for training the clas

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隐士

High Resolution Satellite Classification with Graph Cut Algorithms k-means algorithm, as graph cuts introduce spatial domain information of the image that is lacking in the k-means. High resolution satellite imagery, IKONOS, and SPOT-5 have been evaluated by the proposed method, showing that graph cuts improve k-means results, which in turn show coherent and conti

Aqueous-Humor

Satellite Image Segmentation Using Wavelet Transforms Based on Color and Texture Featuresnt regions of interest. This work presents a novel image segmentation method based on wavelet transforms for extracting a number of color and texture features from the images. Traditional feature extraction techniques based on individual pixels usually demand high computational cost. To reduce such

ANNUL

A System for Rapid Interactive Training of Object Detectorso lighting, viewpoint, and pose. Generating sufficiently large labeled data sets to support accurate training is often the most challenging problem. To address this, the active learning paradigm suggests interactive user input, creating an initial classifier based on a few samples and refining that

名字的误用

An Integrated Method for Multiple Object Detection and Localization, substantial occlusion and significant scale changes. Our approach consists of first generating a set of hypotheses for each object using a generative model (pLSA) with a bag of visual words representing each image. Then, the discriminative part verifies each hypothesis using a multi-class SVM clas

沟通

A Context Dependent Distance Measure for Shape Clusteringson: clusters are generated in the context of a reference shape, defined by the query shape it is compared to. Tightly coupled, the distance measure is the basis for a soft .-means like framework to achieve robust clustering. Successful application of the system along with generation of shape protot

朝圣者

A New Accumulator-Based Approach to Shape Recognition errors tend to average out. Furthermore, such methods are intrinsically parallel. It is demonstrated to perform better than any competing technique, and is particularly robust under partial occlusion. Its performance is demonstrated in applications of silhouette and face recognition using only edge

装入胶囊

Multi-dimensional Scale Saliency Feature Extraction Based on Entropic Graphs-entropy estimation. The original Kadir and Brady algorithm is conditioned by the curse of dimensionality when estimating entropy from multi-dimensional data like RGB intensity values. Our approach naturally allows to increase dimensionality, being its computation time slightly affected by the numbe

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