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This paper presents a new algorithm for automatically measuring fire spreading characteristics by means of a stereovision system. The proposed framework is based on the use of a pre-calibrated trinocular stereo camera. The first and second steps permit the segmentation and features detection in the images. The third step is a stereo matching approach used in order to automatically process successive...
A method of object detecting based on local contour learning and matching is proposed. Firstly, the representative images are obtained through unsupervised clustering to be as templates. The local contour information of template is extracted and generalized as the template feature, at the same time, codebook dictionary of local contour is built up. Secondly, based on codebook dictionary, using simple...
Template matching technology has been widely used in FLIR guiding. When using FLIR guiding weapon attack targets, the target imaging in the FLIR lens will be distorted by size and shape. In order to prepare the corresponding dynamic template, it proposes a new target dynamic template preparation method using the simulated 3-D scene of the target and the weapon flight track. Based on that method, an...
To find the corresponding target points among multi-images of the same scene is a premise of three dimensional (3D) reconstruction automatically from multi-view images. The geometrical constraints among multi-images of the same scene are analyzed and it is concluded that the error matching cannot be removed if only using 2D information. In this paper, we present an iterative fractional step matching...
We present a novel object detection framework that uses the local shape patches features combining the interclass global features information. A supervised local model learning architecture is proposed: a novel interest point descriptor is proposed and applied to detect the local shape patches, the local shape patches are formed by chains of several connected contour segments. Then the object local...
This paper presents a novel 3D shape retrieval method, which uses Bag-of-Features and an efficient multi-view shape matching scheme. In our approach, a properly normalized object is first described by a set of depth-buffer views captured on the surrounding vertices of a given unit geodesic sphere. We then represent each view as a word histogram generated by the vector quantization of the view's salient...
In this paper, we propose a novel face representation in which a face is represented in terms of dense Scale Invariant Feature Transform (d-SIFT) and shape contexts of the face image. The application of the representation in gender recognition has been investigated. There are four problems when applying the SIFT to facial gender recognition. (1) There may be only a few keypoints that can be found...
IGES is a widely used standard for mechanical data exchange. In this paper, we present a new method for the retrieval task of IGES surface model. Based on this method, a novel distinctive face selection strategy is proposed and evaluated. In the training database, each model is treated as a set of disordered faces, and their features are extracted and stored respectively. The Discounted Cumulative...
A great deal of descriptors for region matching have been proposed in last years. However, an extra step, fitting the irregular regions into fixed shapes, must be implemented in advance when constructing these descriptors on irregular regions. This fitting step can cause great errors, and thus will result in poor matching. Base on inner product and exterior product, this paper develops a method for...
We describe a method to compute the prototypical shapes for object categories using the shock graph representation. Given a set of category exemplars, we determine a prototypical shape for this category by estimating the Karcher mean of the shock graphs of the exemplar shapes. The method is described in three steps. First, we derive an iterative method to average N points in an abstract continuous...
Palmprint verification is a relatively new but promising personal authentication technique for its high accuracy and fast matching speed. Two dimensional (2D) palmprint recognition has been well studied in the past decade, and recently three dimensional (3D) palmprint recognition techniques were also proposed. The 2D and 3D palmprint data can be captured simultaneously and they provide different and...
Many of the recently popular shape based category recognition methods require stable, connected and labeled edges as input. This paper introduces a novel method to find the most stable region boundaries in grayscale images for this purpose. In contrast to common edge detection algorithms as Canny, which only analyze local discontinuities in image brightness, our method integrates mid-level information...
We study the object localization problem in images given a single hand-drawn example or a gallery of shapes as the object model. Although many shape matching algorithms have been proposed for the problem over the decades, chamfer matching remains to be the preferred method when speed and robustness are considered. In this paper, we significantly improve the accuracy of chamfer matching while reducing...
An image search for “clownfish” yields many photos of clownfish, each of a different individual of a different 3D shape in a different pose. Yet, to the human observer, this set of images contains enough information to infer the underlying 3D deformable object class. Our goal is to recover such a deformable object class model directly from unordered images. For classes where feature-point correspondences...
We present a feature matching algorithm that leverages bottom-up segmentation. Unlike conventional image-to-image or region-to-region matching algorithms, our method finds corresponding points in an “asymmetric” manner, matching features within each region of a segmented image to a second unsegmented image. We develop a dynamic programming solution to efficiently identify corresponding points for...
We recognize actions and activities in video sequences as distinguishing patterns in the 3D spatiotemporal volume of motion energy. Local motion descriptors, which capture highly discriminative invariant motion characteristics in a spherical neighborhood, are computed in the 3D volume at points of salient motion to represent actions or activities in video sequences. Two actions are then matched based...
In this paper we address the problem of matching two 3D shapes by representing them using the eigenvalues and eigenvectors of the discrete diffusion operator. This provides representation framework useful for scale-space local shape descriptors and shape comparisons. We formally introduce diffusion embedding and we propose unit hypersphere normalizations of this embedding. We also propose a method...
In this paper, based on manifold harmonics, we propose a novel framework for 3D shape similarity comparison and partial matching. First, we propose a novel symmetric mean-value representation to robustly construct high-quality manifold harmonic bases on nonuniform-sampling meshes. Then, based on the manifold harmonic bases constructed, a novel shape descriptor is presented to capture both of global...
It has been shown that the 3D shape of a deformable surface in an image can be recovered by establishing correspondences between that image and a reference one in which the shape is known. These matches can then be used to set-up a convex optimization problem in terms of the shape parameters, which is easily solved. However, in many cases, the correspondences are hard to establish reliably. In this...
For various 3D shape analysis tasks, the Laplace-Beltrami(LB) embedding has become increasingly popular as it enables the efficient comparison of shapes based on intrinsic geometry. One fundamental difficulty in using the LB embedding, however, is the ambiguity in the eigen-system, and it is conventionally only handled in a heuristic way. In this work, we propose a novel and intrinsic metric, the...
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