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Segmentation and grouping of image elements is required to proceed with image recognition. Due to the fact that the images are two dimensional (2D) representations of the real three dimensional (3D) scenes, the information of the third dimension, like geometrical relations between the objects that are important for reasonable segmentation and grouping, are lost in 2D image representations. Computer...
In this paper, we present a key point recognition scheme, which consists of a novel feature detector and an efficient descriptor. Inspired by FAST (features from accelerated segment test), our feature detector is easy to compute and has high repeatability. Scale-invariance and optimized robustness are gained by extending traditional FAST to scale space.We combine this detector with an adapted version...
For the purpose of color image segmentation, an unsupervised peak value searching algorithm was proposed, which was used to determine the approximate dominant color components of image. First, the local peaks of 3D color histogram within the neighborhood of 3 times 3 times 3 were located. The corresponding color values of local peaks were regarded as initial clustering centers, and the number of local...
Finding traversable paths using computer vision is one of the most important components of an intelligent mobile robot system. For a wall climbing robot that operates in an urban environment, it is essential to automatically detect surface types and orientations for switching between moving and climbing, and for applying different adhesive forces both to save energy and ensure its own safety. This...
Depth perception, or 3D perception, can add a lot to the feeling of immersiveness in many applications such as 3D TV, 3D teleconferencing, etc. Stereopsis and motion parallax are two of the most important cues for depth perception. Most of the 3D displays today rely on stereopsis to create 3D perception. In this paper, we propose to improve user's depth perception by tracking their motions and creating...
This paper presents a feature based 3D mapping approach with regard to obtaining compact models of semi-structured environments such as partially destroyed buildings where mobile robots are to carry out rescue activities. To gather the 3D data, we use a laser scanner, employing a nodding data acquisition system mounted on both real and simulated robots. Our segmentation algorithm comes up from the...
Detection of linear structure is a very important problem in image processing and computer vision. The task of finding lines in 2D images has long being studied, but the work in 3D space does not have any promising work yet. This paper investigates the issue of line detection for range images. It proposes an approach to find a wire-frame composed of lines that can represent precisely and comprehensively...
In this work, a modified Fourier Transform Profilometry method, together with the region post-processing (where the object to digitize is located) is used as a 3D reconstruction system for solid objects. By projecting a sinusoidal fringe pattern with a known spatial frequency on the object, a vision system is capable of infer the object's depth information. First, the fringe pattern is projected on...
In this paper, we address the problem of segmenting data defined on a manifold into a set of regions with uniform properties. In particular, we propose a numerical method when the manifold is represented by a triangular mesh. Based on recent image segmentation models, our method minimizes a convex energy and then enjoys significant favorable properties: it is robust to initialization and avoid the...
We present a novel variant of the RANSAC algorithm that is much more efficient, in particular when dealing with problems with low inlier ratios. Our algorithm assumes that there exists some grouping in the data, based on which we introduce a new binomial mixture model rather than the simple binomial model as used in RANSAC. We prove that in the new model it is more efficient to sample data from a...
Perceiving dynamic scenes of rigid bodies, through affine projections of moving 3D point clouds, boils down to clustering the rigid motion subspaces supported by the points' image trajectories. For a physically meaningful interpretation, clusters must be consistent with the geometry of the underlying subspaces. Most of the existing measures for subspace clustering are ambiguous, or geometrically inconsistent...
This paper presents a method for fitting a digital plane to a given set of points in a 3D image in the presence of outliers. We present a new method that uses a digital plane model rather than the conventional continuous model. We show that such a digital model allows us to efficiently examine all possible consensus sets and to guarantee the solution optimality and exactness. Our algorithm has a time...
Subspace segmentation is the task of segmenting data lying on multiple linear subspaces. Its applications in computer vision include motion segmentation in video, structure-from-motion, and image clustering. In this work, we describe a novel approach for subspace segmentation that uses probabilistic inference via a message-passing algorithm. We cast the subspace segmentation problem as that of choosing...
This paper presents a vision-based road-barriers detection method. Because horizontal structures are hard to detect by binocular stereovision, object detection methods based on 3D points grouping fail to detect the barriers as obstacles and consequently specific ACC applications as longitudinal control will fail to react when the vehicle path is obstructed by such an object. Therefore the proposed...
In this paper, we present a new robust camera pose estimation approach based on 3D lines tracking. We used an extended Kalman filter (EKF) to incrementally update the camera pose in real-time. The principal contributions of our method includes first, the expansion of the RANSAC scheme in order to achieve a robust matching algorithm that associates 2D edges from the image with the 3D line segments...
A new region-based depth ordering algorithm is proposed based on the segmented motion layers with affine motion models. Starting from an initial set of layers that are independently extracted for each frame of an input sequence, relative depth order of every layer is determined following a bottom-to-top approach from local pair-wise relations to a global ordering. Layer sets of consecutive time instants...
Computer-aided detection (CAD) systems, which automatically detect and indicate location of potential abnormalities in scan digital images, have the capacity to increase the accuracy of the radiologistspsila interpretations and finding. This paper presents an efficient new CAD for automatic and accurate detection and quantification of abdominal aortic aneurysm (AAA). The system first detects and extracts...
Motion capture serves as a key technology in a wide spectrum of applications, including interactive game and learning, animation, film special effects, health-care and navigation. The existing human motion capture techniques, which use structured multiple high resolution cameras in the dedicated studio, are complicated and expensive. As rapid development of micro inertial sensors-on-chip, ubiquitous,...
Body language is a connection way between humans. Computer vision based system try to facilitate human connections using human gesture interpretations. This paper proposes a method based on hand gesture recognition for device control using inner distance feature. Our method consists of three primary parts. 1) Hand segmentation and state identification. 2) Hand tracking, and 3) gesture recognition...
3-D reconstruction from medical images is an important application of computer graphics and biomedicine image processing. Image segmentation is a crucial step in 3-D reconstruction. In this paper, an improved image segmentation method which is suitable for 3-D reconstruction is put forward. A 3-D reconstruction algorithm is used to reconstruct the 3-D model from images. First, rough edge is extracted...
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