We present a neural network-based face detection system. A retinally connected neural network examines small windows of an image, and decides whether each window contains a face. The system arbitrates between multiple...
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ISBN:
(纸本)0818672587
We present a neural network-based face detection system. A retinally connected neural network examines small windows of an image, and decides whether each window contains a face. The system arbitrates between multiple networks to improve performance over a single network. We use a bootstrap algorithm for training the networks, which adds false detections into the training set as training progresses. This eliminates the difficult task of manually selecting non-face training examples, which must be chosen to span the entire space of non-face images. Comparisons with other state-of-the-art face detection systems are presented;our system has better performance in terms of detection and false-positive rates.
In this paper we present a novel approach to surface recovery from an image sequence of a rotating object. In this approach, the object is illuminated under a collinear light source (where the light source lies on or ...
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ISBN:
(纸本)0818672587
In this paper we present a novel approach to surface recovery from an image sequence of a rotating object. In this approach, the object is illuminated under a collinear light source (where the light source lies on or near the optical axis) and rotated on a controlled turntable. A wire-frame of 3D curves on the object surface is extracted by using shading and occluding contours in the image sequence. Then the whole object surface is recovered by interpolating the surface between curves on the wire-frame. The interpolation can be done by using geometric or photometric constraints. The photometric method uses shading information and is more powerful than geometric methods. The experimental results on real image sequence of matte and specular surfaces show that the technique is feasible and promising.
Many presume that parsing the shadows out of an image is a high-level task, because of the global nature of the shadow formation process. But shape-from-shading algorithms are low-level, in the sense that they seek so...
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ISBN:
(纸本)0818672587
Many presume that parsing the shadows out of an image is a high-level task, because of the global nature of the shadow formation process. But shape-from-shading algorithms are low-level, in the sense that they seek solutions (surface normals or depth values) directly from image intensities. A dilemma arises: since shape-from-shading involves an illumination term, shadows must first be identified. We show that a structure intermediate between intensities and surfaces - the shading flow field - provides a solution to this dilemma. Our analysis is based on the observation that the geometric information that can be derived from images supports different inferences than the photometric information, and our specific goal will be to articulate this geometric structure and to show how shading flow fields can be reliably computed.
In this paper;we present a neural network-based face detection system. Unlike similar systems which nr-e limited to detecting upright,frontal faces, this system detects faces at any degree of rotation in the image pla...
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ISBN:
(纸本)0818684976
In this paper;we present a neural network-based face detection system. Unlike similar systems which nr-e limited to detecting upright,frontal faces, this system detects faces at any degree of rotation in the image plane. The system employs multiple networks;a "router" network first processes each input window to determine its orientation and then uses this information to prepare the window for one or more "detector" networks. We present the training methods for. both types of networks. We also perform sensitivity analysis an the networks, and present empirical results on a large test set. Finally! we present preliminary results for detecting faces rotated out of the image plane, such as profiles and semi-profiles.
A common factor in all illusory contour figures is the perception of a surface occluding part of a background. In our previous work, we have shown we could diffuse a proper set of junction hypothesis (what is salient ...
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ISBN:
(纸本)0818672587
A common factor in all illusory contour figures is the perception of a surface occluding part of a background. In our previous work, we have shown we could diffuse a proper set of junction hypothesis (what is salient or background) to obtain a surface where their boundaries represented illusory contours. Amodal completions emerge at the overlapping surfaces. We address the problem of selecting the best image organization (set of hypothesis). We propose an optimization criteria based on a coherence measure between pairs of junctions (correlation between the diffusion of each pair). A statistical physics approach to select the best organization is applied. The experiments suggest that despite the large number of possible organizations our approach may take only a few steps (in organization space) to select the best one.
The success of an intelligent robotic system depends on the performance of its vision-system which in turn depends to a great extend upon the quality of its calibration. During the execution of a task the vision-syste...
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ISBN:
(纸本)0780342364
The success of an intelligent robotic system depends on the performance of its vision-system which in turn depends to a great extend upon the quality of its calibration. During the execution of a task the vision-system is subject to external influences such as vibrations, thermal expansion etc. which affect and possibly render invalid the initial calibration. Moreover it is possible that the parameters of the vision-system like e.g. the zoom or the focus are altered intentionally in order to perform specific vision-tasks. This paper describes a technique for automatically maintaining calibration of stereovision systems over time without using again any particular calibration apparatus. It uses all available information, i.e. both spatial and temporal data. Uncertainty is systematically manipulated and maintained. Synthetical and real data are used to validate the proposed technique, and the results compare very favourably with those given by classical calibration methods.
In this paper we propose a new distance measure for an identification problem and describe experiments on fingerprints preselection using eigenfeatures of ridge direction patterns. The distance is defined by likelihoo...
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ISBN:
(纸本)0818684976
In this paper we propose a new distance measure for an identification problem and describe experiments on fingerprints preselection using eigenfeatures of ridge direction patterns. The distance is defined by likelihood ratio of error distribution of feature vectors to the whole distribution of feature vector differences. In addition, we introduce "quality indexes" of feature vectors and make the distance adaptive to the quality indexes. Experiments on fingerprint preselection for ten-print cards revealed that our proposed distance is much more effective than the Mahalanobis distance. By combining the eigenfeatures and traditional classification features;0.06% false acceptance rate at 2.0% false rejection rate and one million cards/sec preselection speed on a standard workstation, have been achieved. This makes it possible to construct high performance fingerprint identification systems.
Correlation-based real-time stereo systems have been proven to be effective in applications such as robot navigation, elevation map building etc. This paper provides an in-depth analysis of the major error sources for...
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ISBN:
(纸本)0780342364
Correlation-based real-time stereo systems have been proven to be effective in applications such as robot navigation, elevation map building etc. This paper provides an in-depth analysis of the major error sources for such a real-time stereo system in the context of cross-country navigation of an autonomous vehicle. Three major types of errors: foreshortening error, misalignment error and systematic error, are identified. The combined disparity errors can easily exceed three-tenths of a pixel, which translates to significant range errors. Upon understanding these error sources, we demonstrate different approaches to either correct them or model their magnitudes without excessive additional computations. By correcting those errors, we show that the precision of the stereo algorithm can be improved by 50%.
We study occluding contour artifacts in area-based stereo matching: they are false responses of the matching operator to the occlusion boundary and cause the objects extend beyond their true boundaries in disparity ma...
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ISBN:
(纸本)0780342364
We study occluding contour artifacts in area-based stereo matching: they are false responses of the matching operator to the occlusion boundary and cause the objects extend beyond their true boundaries in disparity maps. Most of the matching methods suffer from these artifacts;the effect is so strong that it cannot be ignored. We show what gives rise to the artifacts and design a matching criterion that accommodates the presence of occlusions as opposed to methods that identify and remove the artifacts. This approach leads to the problem of measurement contamination studied in statistics. We show that such a problem is hard given finite computational resources, unless more independent measurements directly related to occluding contours is available. What can be achieved is a substantial reduction of the artifacts, especially for large matching templates. Reduced artifacts allow for easier hierarchical matching and for easy fusion of reconstructions from different viewpoints into a coherent whole.
We investigate the problem of recognizing words from video, fingerspelled using the British Sign Language (BSL) fingerspelling alphabet. This is a challenging task since the BSL alphabet involves both hands occluding ...
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ISBN:
(纸本)9781424439942
We investigate the problem of recognizing words from video, fingerspelled using the British Sign Language (BSL) fingerspelling alphabet. This is a challenging task since the BSL alphabet involves both hands occluding each other and contains signs which are ambiguous from the observer's viewpoint. The main contributions of our work include: (i) recognition based on hand shape alone, not requiring motion cues;(ii) robust visual features for hand shape recognition;(iii) scalability to large lexicon recognition with no re-training. We report results on a dataset of 1,000 low quality web-cam videos of 100 words. The proposed method achieves a word recognition accuracy of 98.9%.
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