The ability to classify age from a facial image has not been pursued in computervision. This research addresses the limited task of age classification of a facial image into a baby, young adult, and senior adult. Thi...
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The ability to classify age from a facial image has not been pursued in computervision. This research addresses the limited task of age classification of a facial image into a baby, young adult, and senior adult. This is the first reported work to classify age, and to successfully extract and use natural wrinkles. We present a theory and practical computations for visual age classification from facial images, based on cranio-facial changes in feature-position ratios, and on skin wrinkle analysis. Three age groups are classified.< >
The use of a small set of features is recurrent in the object recognition literature. If the image data is perfect with no sensor uncertainty and there are not incorrect feature correspondences between the model and t...
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The use of a small set of features is recurrent in the object recognition literature. If the image data is perfect with no sensor uncertainty and there are not incorrect feature correspondences between the model and the image, then the pose of the object can be computed with no error using these few correspondences. However, in most real cases the noise in the data will propagate into the pose. Moreover, the extent of the effect of the uncertainty will depend on the selection of the correspondences used to compute it. In this paper we address the problem of how to select these correspondences so that the effect of the data uncertainty on the pose estimation is minimized.< >
A system for the interpretation of telephone company drawings is described. Two different types of drawings are interpreted: manhole and table drawings. Each drawing is interpreted by using a different approach to sui...
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A system for the interpretation of telephone company drawings is described. Two different types of drawings are interpreted: manhole and table drawings. Each drawing is interpreted by using a different approach to suit its characteristics. Manhole drawings represent the interconnection of telephone lines in the field. The approach used is the vectorization of the line segments to extract continuous lines. The table drawings contain information related to the cables in the manhole. The approach is to locate lines and their intersections to extract the information for entries. An Intelligent Character recognition (ICR) system is used to interpret text information by using grammars.< >
This paper is based on the observation that if the viewing camera is appropriately mounted on a vehicle which moves on a planar surface, the problem of motion and structure recovery from optical flow becomes linear an...
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This paper is based on the observation that if the viewing camera is appropriately mounted on a vehicle which moves on a planar surface, the problem of motion and structure recovery from optical flow becomes linear and, in principle, can be solved locally. It is shown that angular velocity and depth can be computed from one component only of the optical flow, and that the accuracy in the estimation of depth from the vertical component is more accurate than that from the horizontal component. Experiments on synthetic and real sequences support the presented analysis.< >
This paper deals with the recovery of 3D information using a single mobile camera in the context of active vision. We propose a general revisited formulation of the structure-from-motion issue, and we determine adequa...
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This paper deals with the recovery of 3D information using a single mobile camera in the context of active vision. We propose a general revisited formulation of the structure-from-motion issue, and we determine adequate camera configurations and motions which lead to a robust and accurate estimation of the 3D structure parameters. We apply the visual servoing approach to perform these camera motions. Real-time experiments dealing with the 3D structure estimation of points and cylinders are reported, and demonstrate that this active vision strategy can very significantly improve the estimation accuracy.< >
This paper presents a Radon transform-based approach to the detection of linear features in images characterized by high noise levels. This approach is based on the localized Radon transform where the intensity integr...
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This paper presents a Radon transform-based approach to the detection of linear features in images characterized by high noise levels. This approach is based on the localized Radon transform where the intensity integration is performed over short line segments rather than across the entire image. The algorithm, referred to as the feature space line detector (FSLD) algorithm, is tested on synthetic images of linear features with very high noise levels. The results of this testing demonstrate the algorithm's robustness in the presence of noise, as well as its ability to detect and localize linear features that are significantly shorter than the image dimensions or that display some curvature.< >
When recognizing a fixed object from a fixed viewpoint, the dominant source of variation in image intensity is lighting changes. We propose a low-dimensional model for human faces that can both synthesize a face image...
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When recognizing a fixed object from a fixed viewpoint, the dominant source of variation in image intensity is lighting changes. We propose a low-dimensional model for human faces that can both synthesize a face image when given lighting conditions and can estimate lighting conditions when given a face image. The model can handle non-Lambertian and self-shadowing surfaces such as faces because it does not make any assumptions about either the surface geometry or bidirectional reflectance function. The model can be adapted to handle any arbitrary lighting condition, and is easily extendable to any other viewpoint or to any other object.< >
The problem of object recognition is addressed. In the literature this task has been generally considered in a "passive" perspective, where everything is static and there is no definite relation between the ...
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The problem of object recognition is addressed. In the literature this task has been generally considered in a "passive" perspective, where everything is static and there is no definite relation between the object and its environment. We propose an "active" approach for object recognition, based on the capability of the observer to move and give a better description of the object under consideration and also to take advantage of the relations between the objects and the environment. This can be accomplished at the task level and at the sensor level. The face recognition problem, based on the face-space approach, is considered to demonstrate the advantage of adopting an active retina to sample the face, build a database and perform the recognition task. By using an active space-variant retina the size of the database is considerably reduced and consequently the processing time for recognition. A comparative experiment using the active and static approach is presented.< >
This paper proposes an effective next view planning strategy for the object recognition and localization task in a model-based robot vision system. A set of rules are designed to automatically predict new features and...
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ISBN:
(纸本)0818658258
This paper proposes an effective next view planning strategy for the object recognition and localization task in a model-based robot vision system. A set of rules are designed to automatically predict new features and calculate the next optimal placement of the sensor so that the most useful information can be gathered from multi-views. A state vector (i,r,t) is defined to describe the current state of the vision system and each possible state corresponds to a subset of rules to deal with it. The recognition and location task can be described as a process of rule calling and state conversions. The most suitable rule is selected at each step to try to acquire more useful information as soon as possible. Experiments are shown in the paper.< >
The trade-off between the granularity of the data representation and the recognition accuracy is examined in this paper. We show that unless a particular criterion is satisfied, there is no guarantee of achieving a pr...
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The trade-off between the granularity of the data representation and the recognition accuracy is examined in this paper. We show that unless a particular criterion is satisfied, there is no guarantee of achieving a prescribed recognition accuracy. This criterion of interest, is the mutual information content between the measurements and the class identities. A novel method for the objective evaluation of intrinsic error in recognition as sampling rate varies, is described. This approach is general enough to permit the evaluation of error even when the parameter under study takes a different form. To demonstrate this we present results in feature subset selection and multiple classifier combination. In the case of feature selection, the measurements are the features. In the case of multiple classifier combination it is the "quality" of the individual classifiers, evalulated based on the mutual information between the classifier parameters and class identities.< >
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