We introduce the concept of a spatiogram, which is a generalization of a histogram that includes potentially higher order moments. A histogram is a zeroth-order spatiogram, while second-order spatiograms contain spati...
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ISBN:
(纸本)0769523722
We introduce the concept of a spatiogram, which is a generalization of a histogram that includes potentially higher order moments. A histogram is a zeroth-order spatiogram, while second-order spatiograms contain spatial means and covariances for each histogram bin. This spatial information still allows quite general transformations, as in a histogram, but captures a richer description of the target to increase robustness in tracking. We show how to use spatiograms in kernel-based trackers, deriving a mean shift procedure in which individual pixels vote not only for the amount of shift but also for its direction. Experiments show improved tracking results compared with histograms, using both mean shift and exhaustive local search.
We present a set of algorithms and a search strategy for the robust content-based retrieval of multispectral satellite images. Since the property of interest in these images is usually the physical characteristics of ...
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ISBN:
(纸本)0818672587
We present a set of algorithms and a search strategy for the robust content-based retrieval of multispectral satellite images. Since the property of interest in these images is usually the physical characteristics of ground cover, we use representations and methods that are invariant to illumination and atmospheric conditions. The representations and algorithms are derived for this application from a physical model for the formation of multispectral satellite images. The use of several representations and algorithms is necessary to interpret the diversity of physical and geometric structure in these images. Algorithms are used that exploit multispectral distributions, multispectral spatial structure, and labeled classes. The performance of the system is demonstrated on a large set of multispectral satellite images taken over different areas of the United States under different illumination and atmospheric conditions.
In this paper we present a novel learning based method for restoring and recognizing images of digits that have been blurred using an unknown kernel. The novelty of our work is an iterative loop that alternates betwee...
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We study the problem of estimating rigid motion from a sequence of monocular perspective images obtained by navigating around an object while fixating a particular feature point. We cast the problem in the framework o...
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ISBN:
(纸本)0818672587
We study the problem of estimating rigid motion from a sequence of monocular perspective images obtained by navigating around an object while fixating a particular feature point. We cast the problem in the framework of "epipolar geometry", and propose a filter based upon implicit dynamical model for recursively estimating motion under the fixation constraint. This allows us to compare the quality of the estimates directly against the ones obtained assuming a general rigid motion simply by changing the geometry of the parameter space, while maintaining the same structure of the recursive estimator. We also present a closed-form static solution from two views, and a recursive estimator of the relative pose between the viewer and the scene.
Automatic video browsing requires algorithms for detecting a variety of events, including production effects (e.g., scene breaks and captions) and moving objects. We present new methods that use edges and motion for d...
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ISBN:
(纸本)0818672587
Automatic video browsing requires algorithms for detecting a variety of events, including production effects (e.g., scene breaks and captions) and moving objects. We present new methods that use edges and motion for detecting production effects and computing motion segmentation. Production effects, such as cuts, dissolves, wipes and captions, can be detected by looking for new edges that are far from previous edges. A global motion computation is used to register consecutive images. We have also developed a method for motion segmentation, which does not require computing local optical flow. Our methods run at several frames per second on a Sparc workstation, and tolerate compression artifacts.
Planar pose measurement from images is an important problem for automated assembly and inspection. In addition to accuracy and robustness, ease of use is very important for real world applications. Recently, Murase an...
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ISBN:
(纸本)0818672587
Planar pose measurement from images is an important problem for automated assembly and inspection. In addition to accuracy and robustness, ease of use is very important for real world applications. Recently, Murase and Nayar have presented the 'parametric eigenspace' for object recognition and pose measurement based on training images. Although their system is easy to use, it has potential problems with background clutter and partial occlusions. We present an algorithm that is robust in these terms. It uses several small features on the object rather than a monolithic template. These 'eigenfeatures' are matched using a median statistic, giving the system robustness in the face of background clutter and partial occlusions. We demonstrate our algorithm's pose measurement accuracy with a controlled test, and we demonstrate its detection robustness on cluttered images with the objects of interest partially occluded.
Motion of an observer relative to objects in a scene provides information about the structure of the scene. Changing patterns of shading due to motion relative to the light source provide information about surface str...
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ISBN:
(纸本)0818672587
Motion of an observer relative to objects in a scene provides information about the structure of the scene. Changing patterns of shading due to motion relative to the light source provide information about surface structure, albedos, and light sources. One can stratify this photometric information into affine, unitary, and metric structure, much like the stratification of structure from motion [1]. For Lambertian surfaces, if either motion or photometry give us more than affine structure, the two cues can be combined to yield full metric information. Edge constraints plus unitary photometry also give us full metric photometry. Affine structure alone contains much of the quantitative structure information, allowing us to judge such things as the ordinal relationships between the albedos.
We develop and demonstrate an object recognition system capable of accurately detecting, localizing, and recovering the kinematic configuration of textured animals in real images. We build a deformation model of shape...
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ISBN:
(纸本)0769523722
We develop and demonstrate an object recognition system capable of accurately detecting, localizing, and recovering the kinematic configuration of textured animals in real images. We build a deformation model of shape automatically from videos of animals and an appearance model of texture from a labeled collection of animal images, and combine the two models automatically. We develop a simple texture descriptor that outperforms the state of the art. We test our animal models on two datasets;images taken by professional photographers from the Corel collection, and assorted images from the web returned by Google. We demonstrate quite good performance on both datasets. Comparing our results with simple baselines, we show that for the Google set, we can recognize objects from a collection demonstrably hard for object recognition.
We present the Incremental Focus of Attention (IFA) architecture for adding robustness to software-based, real-time, motion trackers. The framework provides a structure which, when given the entire camera image to sea...
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ISBN:
(纸本)0818672587
We present the Incremental Focus of Attention (IFA) architecture for adding robustness to software-based, real-time, motion trackers. The framework provides a structure which, when given the entire camera image to search, efficiently focuses the attention of the system into a narrow set of possible states that includes the target state. IFA offers a means for automatic tracking initialization and reinitialization when environmental conditions momentarily deteriorate and cause the system to lose track of its target. Systems based on the framework degrade gracefully as various assumptions about the environment are violated. In particular, multiple tracking algorithms are layered so that the failure of a single algorithm causes another algorithm of less precision to take over, thereby allowing the system to return approximate feature state information.
A method that combines shape-based object recognition and image segmentation is proposed for shape retrieval from images. Given a shape prior represented in a multiscale curvature form, the proposed method identifies ...
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ISBN:
(纸本)0769523722
A method that combines shape-based object recognition and image segmentation is proposed for shape retrieval from images. Given a shape prior represented in a multiscale curvature form, the proposed method identifies the target objects in images by grouping oversegmented image regions. The problem is formulated in a unified probabilistic framework, and object segmentation and recognition are accomplished simultaneously by a stochastic Markov Chain Monte Carlo (MCMC) mechanism. Within each sampling move during the simulation process, probabilistic region grouping operations are influenced by both the image information and the shape similarity constraint. The latter constraint is measured by a partial shape matching process. A generalized cluster sampling algorithm [11, combined with a large sampling jump and other implementation improvements, greatly speeds up the overall stochastic process. The proposed method supports the segmentation and recognition of multiple occluded objects in images. Experimental results are provided for both synthetic and real images.
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