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A novel stereo matching algorithm using image segmentation is proposed in this paper. We investigate disparity distribution models (DDMs) on each segment for achieving very high quality results quickly without global optimization. A novel disparity plane fitting strategy based on the investigation is developed for accurately estimating disparity planes. We assign a frontal horizontal disparity plane...
We consider the optimization problem of object recognition for real world images. Although several approaches have been proposed, this paper aims to improve the recognition rate with our novel method. In this paper, a full pixel matching based object recognition method in which no advance segmentation procedure is occurred during matching procedure is proposed. Our method compares the similarity of...
Watershed algorithm as was proposed by Vincent and Soille is an elegant formalism for image segmentation. Watershed conventional algorithm finds out peaks in the gradient image and identifies them as contours. Although this technique has proven its efficiency in some previous works, it suffers from over-segmentation problems, due to the fact that it considers in a similar way lower and higher valued...
Image segmentation aims to partition an image into several disjointed regions that are homogeneous with regards to some measures so that subsequent higher level computer vision processing, such as object recognition, image understanding and scene description can be performed. Multi-objective formulations are realistic models for image segmentation because objectives under consideration conflict with...
In the field of neuroanatomy, automatic segmentation of electron microscopy images is becoming one of the main limiting factors in getting new insights into the functional structure of the brain. We propose a novel framework for the segmentation of thin elongated structures like membranes in a neuroanatomy setting. The probability output of a random forest classifier is used in a regular cost function,...
In the background of specific environmental effects' realization in common visualization system, we analyze current implementation strategy of special effects and disadvantages in emulation. Accord to the features of virtual environment, we design an optimization which can simulate special effects basing on DirectX in visualization system. As the same time, using the examples of water wave effects,...
Given very few images containing a common object of interest under severe variations in appearance, we detect the common object and provide a compact visual representation of that object, depicted by a binary sketch. Our algorithm is composed of two stages: (i) Detect a mutually common (yet non-trivial) ensemble of `self-similarity descriptors' shared by all the input images. (ii) Having found such...
Recent studies have shown that machine learning can improve the accuracy of detecting object boundaries in images. In the standard approach, a boundary detector is trained by minimizing its pixel-level disagreement with human boundary tracings. This naive metric is problematic because it is overly sensitive to boundary locations. This problem is solved by metrics provided with the Berkeley Segmentation...
The reconstruction of complete vascular trees from medical images has many important applications. Although vessel detection has been extensively investigated, little work has been done on how connect the results to reconstruct the full trees. In this paper, we propose a novel theoretical framework for automatic vessel connection, where the automation is achieved by leveraging constraints from the...
We propose an approach to speeding up object detection, with an emphasis on settings where multiple object classes are being detected. Our method uses a segmentation algorithm to select a small number of image regions on which to run a classifier. Compared to the classical sliding window approach, this results in a significantly smaller number of rectangles examined, and thus significantly faster...
In this paper we derive formal constraints relating terrain elevation and observed cast shadows. We show how an optimisation framework can be used to refine surface estimates using shadowing constraints from one or more images. The method is particularly applicable to the digital elevation models produced by the Shuttle Radar Topography Mission (SRTM), which have an abundance of voids in mountainous...
This paper proposes an algorithm for the segmentation and rectification of figures and photos in document images. The algorithm requires just a rough user-provided bounding box for the objects in a single-view image. On receiving the user's bounding box, it takes about 1-2 seconds to segment and rectify mega-pixel sized figures. The main feature of the algorithm is a novel segmentation method that...
Two challenges in computer vision are to accommodate noisy data and missing data. Many problems in computer vision, such as segmentation, filtering, stereo, reconstruction, inpainting and optical flow seek solutions that match the data while satisfying an additional regularization, such as total variation or boundary length. A regularization which has received less attention is to minimize the curvature...
Purely bottom-up, unsupervised segmentation of a single image into foreground and background regions remains a challenging task for computer vision. Co-segmentation is the problem of simultaneously dividing multiple images into regions (segments) corresponding to different object classes. In this paper, we combine existing tools for bottom-up image segmentation such as normalized cuts, with kernel...
Automatic facial action unit (AU) detection from video is a long-standing problem in computer vision. Two main approaches have been pursued: (1) static modeling - typically posed as a discriminative classification problem in which each video frame is evaluated independently; (2) temporal modeling - frames are segmented into sequences and typically modeled with a variant of dynamic Bayesian networks...
We present a study on grocery detection using our object detection system, ShelfScanner, which seeks to allow a visually impaired user to shop at a grocery store without additional human assistance. ShelfScanner allows online detection of items on a shopping list, in video streams in which some or all items could appear simultaneously. To deal with the scale of the object detection task, the system...
A number of 3D shape reconstruction algorithms, in particular 3D image segmentation methods, produce their results in the form of binary volumes, where a binary value indicates whether a voxel is associated with the interior or the exterior. For visualization purpose, it is often desirable to convert a binary volume into a surface representation. Straightforward extraction of the median isosurfaces...
Graph-cuts optimization is prevalent in vision and graphics problems. It is thus of great practical importance to parallelize the graph-cuts optimization using today's ubiquitous multi-core machines. However, the current best serial algorithm by Boykov and Kolmogorov (called the BK algorithm) still has the superior empirical performance. It is non-trivial to parallelize as expensive synchronization...
Hierarchical conditional random fields have been successfully applied to object segmentation. One reason is their ability to incorporate contextual information at different scales. However, these models do not allow multiple labels to be assigned to a single node. At higher scales in the image, this yields an oversimplified model, since multiple classes can be reasonable expected to appear within...
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