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Range image recognition gains importance in the recent years due to the developments in acquiring, displaying, and storing such data. In this paper, we present a novel method for matching range surfaces. Our method utilizes local surface properties and represents the geometry of local regions efficiently. Integrating the Scale Invariant Feature Transform (SIFT) with the shape index (SI) representation...
A method to classify tentative feature matches as inliers or outliers to a transformation model is presented. It is well known that ratios of areas of corresponding shapes are affine invariants. Our algorithm uses consistency of ratios of areas in pairs of images to classify matches as inliers or outliers. The method selects four matches within a region, and generates all possible corresponding triangles...
In this paper, we propose a method for projecting images onto non-planar screens by using projector-camera systems eliminating distortion in projected images. In this system, point-to-point correspondences in a projector image and a camera image should be extracted. For finding correspondences, the epipolar geometry between a projector and a camera is used. By using dynamic programming method on epipolar...
Human-area segmentation is a major issue in video surveillance. Many existing methods estimate individual human areas from the foreground area obtained by background subtraction, but the effects of camera movement can make it difficult to obtain a background image. We have achieved human-area segmentation requiring no background image by using chamfer matching to match the results of human detection...
In this paper, we explore the idea of using only pose, without utilizing any temporal information, for human action recognition. In contrast to the other studies using complex action representations, we propose a simple method, which relies on extracting “key poses” from action sequences. Our contribution is two-fold. Firstly, representing the pose in a frame as a collection of line-pairs, we propose...
Water reflection detection is a tough task in computer vision, since the reflection is distorted by ripples irregularly. This paper proposes an effective method to detect water reflections. We introduce a descriptor that is not only invariant to scales, rotations and affine transformations, but also tolerant to the flip transformation and even non-rigid distortions, such as ripple effects. We analyze...
We propose a new circularity measure inspired from Arkin, Latecki tools of shape matching that is constructed in a tangent space. We then introduce a linear algorithm that uses this measure for circularity measuring. This method can also be regarded as a method for circular object recognition. Experimental results show the robustness of this simple method.
Computer assisted medical image processing can extract vital information that may be elusive to human eyes. In this paper, an algorithm is proposed to automatically estimate the position of the actual midline from the brain CT scans using multiple regions shape matching. The method matches feature points identified from a set of ventricle templates, extracted from MRI, with the corresponding feature...
Spatial matching for object retrieval is often time-consuming and susceptible to viewpoint changes. To address this problem, we propose a novel spatial matching method and implement it on modern GPU in parallel. Unlike previous spatial matching methods, in which the affine transformation estimation is based on the gravity vector assumption, our method abandons this strong assumption by matching the...
In this paper, we investigate the problem of automated assembly of shredded pieces from multiple photos. We first establish candidate matchings between fragments by using both shape and appearance information. A weighted graph whose vertices represent shredded pieces and edges represent candidate matchings is then constructed, and divided into separate subgraphs, with each subgraph corresponding to...
Feature matching plays an important role in many applications, including 3D reconstruction, object recognition and video understanding. Point matching has made great progress recently, while it has made little progress in the fields of line and curve matching. By computing statistics of point descriptors constructed at each edge points, this paper develops a novel method for extending point descriptors...
This communication deals with finding the position of a reference shape in a given image. The proposed matcher is constructed from local dissimilarity maps. These maps allow to efficiently and robustly measure the differences between two images. It is shown an example that the matcher potentially returns less false-positives than a reference method (chamfer matching). This is possible as the local...
Generally, computers can successfully achieve object recognition by relying on sufficient information of observed objects. However, in real world, many objects own diverse configurations or objects are observed at various angles and positions, which make it difficult to match the observed objects with data models in a limited database. In this paper, to resolve the above problem, we propose an algorithm...
In this paper we present a novel model-based hybrid technique for user localization and drift-free tracking in urban environments. In outdoor augmented reality, instantaneous 6-DoF user localization is achieved with position and orientation sensors such as GPS and gyroscopes. Initial pose obtained with these sensors is dominated by large positional errors due to coarse granularity of GPS data. Subsequent...
A novel geometry based matching approach is proposed for images with multi objects. In the proposed method, shape and topology ordered graphic is developed to model both shape and structural information for images. Vertexes are used to represent shape attributes, while edges are employed to define structural attributes between objects. The similarity between images is measured with two consecutive...
Most stereo matching algorithms are pixel-based. From the perspective of human stereo vision, setting segment as a processing element is more practical. A new fast stereo matching algorithm based on segmentation with ground control points (GCPs) is presented in this paper. Firstly, an object-oriented segmentation method is used to segment the reference image, which not only considers color characteristics,...
This paper presents my work on computing shape models that are computationally fast and invariant basic transformations like translation, scaling and rotation. In this paper, I propose shape detection using a feature called shape context. Shape context describes all boundary points of a shape with respect to any single boundary point. Thus it is descriptive of the shape of the object. Object recognition...
Image registration is the process of overlaying two or more images of the same scene taken at different times, from different view points, and /or by different sensors. A novel feature-based multi-sensor image registration system is developed. The system consists of two new points: first, edge features are extracted from images, and the features are dilated to suppress some certain kinds of noise...
A novel method of transformation-invariant feature extraction called multi-location saliency pattern is proposed in this paper for object recognition and image matching. Multi-location image features are extracted in salient image points, which indicate image locations with high intensity contrast, region homogeneity and shape saliency. Three distinctive types of fragment descriptors are extracted...
Template selection is often a crucial task for target-detection methods; the Hausdorff distance enhances template matching by implicitly encoding the notion of resemblance. The template-matching technique proposed fits embedded electronic systems for the real-time analysis of visual scenes. Practical implementations demonstrate the approach effectiveness by means of comparative tests on several DSP-based...
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