Lambertian photometric stereo with unknown light source parameters is ambiguous. Provided that the object imaged constitutes a surface, the ambiguity is represented by the group of Generalised Bas-Relief (GBR) transfo...
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ISBN:
(纸本)076952334X
Lambertian photometric stereo with unknown light source parameters is ambiguous. Provided that the object imaged constitutes a surface, the ambiguity is represented by the group of Generalised Bas-Relief (GBR) transformations. We show that this ambiguity is resolved when specular reflection is present in two. images taken under two different light source directions. We identify all configurations of the two directional lights which are singular and show that they can easily be tested for While previous work used optimisation algorithms to apply the constraints implied by the specular reflectance component, we have developed a linear algorithm to achieve this goal. Our theory can be utilised to construct fast algorithms for automatic reconstruction of smooth glossy surfaces.
This paper introduces a simple and efficient representation for natural images. We partition an image into blocks and treat the blocks as vectors in a high-dimensional space. We then fit a piece-wise linear model (i.e...
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ISBN:
(纸本)076952334X
This paper introduces a simple and efficient representation for natural images. We partition an image into blocks and treat the blocks as vectors in a high-dimensional space. We then fit a piece-wise linear model (i.e. a union of affine subspaces) to the vectors at each down-sampling scale. We call this a multi-scale hybrid linear model of the image. The hybrid and hierarchical structure of this model allows us effectively to extract and exploit multi-modal correlations among the imagery data at different scales. It conceptually and computationally remedies limitations of many existing image representation methods that are based on either a fixed linear transformation (e.g. DCT wavelets), an adaptive uni-modal linear transformation (e.g. PCA), or a multi-modal model at a single scale. We will justify both analytically and experimentally why and how such a simple multi-scale hybrid model is able to reduce simultaneously the model complexity and computational cost. Despite a small overhead for the model, our results show that this new model gives more compact representations for a wide variety of natural images under a wide range of signal-to-noise ratio than many existing methods, including wavelets.
Camera calibration and imageprocessing, two important issues of mobile robot navigation, are studied in the present work. image of an object is captured by using a CCD camera and stored in the computer memory with th...
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In this paper, we propose a hybrid Tabu Expectation Maximization (TEM) Algorithm for segmentation of Brain Magnetic Resonance (MR) images in both supervised and unsupervised framewrok. Gaussian Hidden Markov Random Fi...
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In this paper, we investigate the problem of video classification into predefined genre, by combining the evidence from multiple classifiers. It is well known in the pattern recognition community that the accuracy of ...
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The focus of the work presented in this paper is the development of efficient coverage prediction algorithms for fixed wireless system based on low power line of sight communication. As a proof of concept, the perform...
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The focus of the work presented in this paper is the development of efficient coverage prediction algorithms for fixed wireless system based on low power line of sight communication. As a proof of concept, the performance of the algorithm is tested on the corDECT WLL system[1]. We have used a novel approaches to prediction by using some algorithms from imageprocessing to perform coverage prediction efficiently.
In this paper we present a novel system for facilitating the creation of stylized view-dependent 3D animation. Our system harnesses the skill and intuition of a traditionally trained animator by providing a convivial ...
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In this paper we present a novel system for facilitating the creation of stylized view-dependent 3D animation. Our system harnesses the skill and intuition of a traditionally trained animator by providing a convivial sketch based 2D to 3D interface. A base mesh model of the character can be modified to match closely to an input sketch, with minimal user interaction. To do this, we recover the best camera from the intended view direction in the sketch using robust computervision techniques. This aligns the mesh model with the sketch. We then deform the 3D character in two stages-first we reconstruct the best matching skeletal pose from the sketch and then we deform the mesh geometry. We introduce techniques to incorporate deformations in the view-dependent setting. This allows us to set up view-dependent models for animation.
The use of hand gestures has become an important part of human computer interaction (HCI) in recent years. vision-based hand gesture recognition involves visual analysis of hand shape, position and/or movement. Due to...
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ISBN:
(纸本)0780385608
The use of hand gestures has become an important part of human computer interaction (HCI) in recent years. vision-based hand gesture recognition involves visual analysis of hand shape, position and/or movement. Due to co-articulation that occurs during transition from one gesture to the next, problem is encountered in continuous hand gesture recognition. This may be tackled by identifying the key frames in the gesture video sequence. Key frames are the frames that can represent the salient content of a video shot in an abstracted manner. In this paper we present an object-based scheme for key frame extraction using Hausdorff distance and subsequent local motion analysis by angular circular local motion descriptor (ACLM) for gesture representation. We propose a finite state machine (FSM) in which gestures are represented by the sequence of key frames and the corresponding key frame duration. Experimental results obtained demonstrate the effectiveness of our proposed scheme for key frame extraction and subsequent gesture representation.
In this paper, we present a general framework for solving the shape from shading problem for a class of surfaces called implicit surfaces by applying image synthesis techniques from computergraphics. The method relie...
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ISBN:
(纸本)0780384075
In this paper, we present a general framework for solving the shape from shading problem for a class of surfaces called implicit surfaces by applying image synthesis techniques from computergraphics. The method relies on iterative synthesis of images from object descriptions in order to minimize an error function. The technique is illustrated in detail for quadric surfaces, with the ellipsoid as the specific example. The advantage of this approach is that reconstructing the shape of objects from shading is possible even under very general imaging conditions.
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