The proceedings contains 120 papers from the 2004 ieeecomputersocietyconference on computervision And patternrecognition: CVPR 2004 - Volume I. The topics discussed include: restoration of curved document images ...
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The proceedings contains 120 papers from the 2004 ieeecomputersocietyconference on computervision And patternrecognition: CVPR 2004 - Volume I. The topics discussed include: restoration of curved document images through 3D shape modeling;fast wide baseline matching for visual hull;shedding light on stereoscopic segmentation;window-based, discontinuity preserving stereo;space-time video completion and tracking loose-limbed people.
The proceedings contains 138 papers from the 2004 ieeecomputersocietyconference on computervision and patternrecognition, CVPR 2004-Volume 2. The topics discussed include: feature-centric evaluation for efficient...
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The proceedings contains 138 papers from the 2004 ieeecomputersocietyconference on computervision and patternrecognition, CVPR 2004-Volume 2. The topics discussed include: feature-centric evaluation for efficient cascaded object detection;learning methods for generic object recognition and invariance to pose and lighting;searching the web with mobile images for location recognition;controlled modulation imaging;automatic cascade training with perturbation bias;tracking multiple humans in crowded environment;and bayesian face recognition using support vector machine and face clustering.
The proceedings contain 186 papers. The topics discussed include: towards recovery of 3D chromosome structure;object-based visual 3D tracking of articulated objects via kinematic sets;non-rigid motion estimation and s...
The proceedings contain 186 papers. The topics discussed include: towards recovery of 3D chromosome structure;object-based visual 3D tracking of articulated objects via kinematic sets;non-rigid motion estimation and spatio-temporal realignment in FMRI;stochastic meta-descent for tracking articulated structures;gender recognition from walking movements using adaptive three-mode PCA;differential structure in non-linear image embedding functions;semantic-level understanding of human actions and interactions using event hierarchy;fusion of a multiple hypotheses color model and deformable contours for figure ground segmentation in dynamic environments;outlier rejection in deformable model tracking;spline-based motion recovery for 3D surfaces using nonrigid shape properties;and constraints for heterogeneous sensor auto-calibration.
We present a novel interactive system and its user interface for removing objects in digital pictures. Our system consists of two components: (i) (partially supervised/automatic) image segmentation (2], and (ii) (guid...
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ISBN:
(纸本)0769523722
We present a novel interactive system and its user interface for removing objects in digital pictures. Our system consists of two components: (i) (partially supervised/automatic) image segmentation (2], and (ii) (guided) texture synthesis [3].
We present an automotive-grade, real-time, vision-based Driver State Monitor. Upon detecting and tracking the driver's facial features, the system analyzes eye-closures and head pose to infer his/her fatigue or di...
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ISBN:
(纸本)0769523722
We present an automotive-grade, real-time, vision-based Driver State Monitor. Upon detecting and tracking the driver's facial features, the system analyzes eye-closures and head pose to infer his/her fatigue or distraction. This information is used to warn the driver and to modulate the actions of other safety systems. The purpose of this monitor is to increase road safety by preventing drivers from falling asleep or from being overly distracted, and to improve the effectiveness of other safety systems.
The choice of a color space is of great importance for many computervision algorithms (e.g. edge detection and object recognition). It induces the equivalence classes to the actual algorithms. However the problem is ...
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ISBN:
(纸本)0769523722
The choice of a color space is of great importance for many computervision algorithms (e.g. edge detection and object recognition). It induces the equivalence classes to the actual algorithms. However the problem is how to automatically select the color space that produces the best result for a particular task. The subsequent difficulty then is how to obtain a proper weighting scheme for the algorithms so that the results are combined in an optimal setting. To achieve proper color space selection and fusion of feature detectors, in this paper we propose a method that exploits non-perfect correlation between the color models derived from the principles of diversification. As a consequence, the weighting scheme yields maximal color discrimination. The method is verified experimentally for two different feature detectors. The experimental results show that the model provides feature detection results having a discriminative power of 30 percent higher than the standard weighting scheme.
Dimensionality reduction via feature projection has been widely used in patternrecognition and machine learning. It is often beneficial to derive the projections not only based on the inputs but also on the target va...
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ISBN:
(纸本)0769523722
Dimensionality reduction via feature projection has been widely used in patternrecognition and machine learning. It is often beneficial to derive the projections not only based on the inputs but also on the target values in the training data set. This is of particular importance in predicting multivariate or structured outputs. which is an area of growing interest. In this paper we introduce a novel projection framework which is sensitive to both input features and outputs. Based on the derived features prediction accuracy can be greatly improved. We validate our approach in two applications. The first is to model users ' preferences on a set of paintings. The second application is concerned with image categorization where each image may belong to multiple categories. The proposed algorithm produces very encouraging results in both settings.
Landuse classification is an important problem in the remote sensing field. It can be used in a wide range of applications. In this paper we propose a hybrid method fusing edges and regions information for the landuse...
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ISBN:
(纸本)0769523722
Landuse classification is an important problem in the remote sensing field. It can be used in a wide range of applications. In this paper we propose a hybrid method fusing edges and regions information for the landuse classification of multispectral images. It mainly includes the steps of image pre-processing, initial segmentation and region merging. Especially, a novel spatial mean shift procedure is proposed so that some information can be extracted and used in the successive steps. Aiming at the multispectral images processing, we also design a band weighting strategy that give a proper weight to each band adaptively according to the region to be processed. Experimental results on the Landsat TM and ETM+ images validate the performance of the proposed method.
This paper presents an axiomatic approach to corner detection. In the first part of the paper we review five currently used corner detection methods (Harris-Stephens, Forstner Shi-Tomasi, Rohr and Kenney et al.) for g...
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ISBN:
(纸本)0769523722
This paper presents an axiomatic approach to corner detection. In the first part of the paper we review five currently used corner detection methods (Harris-Stephens, Forstner Shi-Tomasi, Rohr and Kenney et al.) for graylevel images. This is followed by a discussion of extending these corner detectors to images with different pixel dimensions such as signals (pixel dimension one) and tomographic medical images (pixel dimension three) as well as different intensity dimensions such as color or LADAR images (intensity dimension three). These extensions are motivated by analyzing a particular example of optical flow in pixel and intensity space with arbitrary dimensions. Placing corner detection in a general setting enables us to state four axioms that any corner detector might reasonably be required to satisfy. Our main result is that only the Shi-Tomasi (and equivalently the Kenney et al. 2-norm detector) satisfy all four of the axioms
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