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Despite the fact that original Iterative Closest Point(ICP) algorithm has been widely used for registration, itcannot tackle the problem when two point clouds are par-tially overlapping. Accordingly, this paper proposes a ro-bust approach for the registration of partially overlappingpoint clouds. Given two initially posed clouds, it firstlybuilds up bilateral correspondence and computes bidirec-tional...
We introduce a novel end-to-end real-time pose-robust 3D face tracking framework from RGBD videos, which is capable of tracking head pose and facial actions simultaneously in unconstrained environment without intervention or pre-calibration from a user. In particular, we emphasize tracking the head pose from profile to profile and improving tracking performance in challenging instances, where the...
This paper addresses the problem of automatic 3D shape segmentation in point cloud representation. Of particular interest are segmentations of noisy real scans, which is a difficult problem in previous works. To guide segmentation of target shape, a small set of pre-segmented exemplar shapes in the same category is adopted. The main idea is to register the target shape with exemplar shapes in a piece-wise...
In this paper, we address the problem of temporal alignment of surfaces for subjects dressed in wide clothing, as acquired by calibrated multi-camera systems. Most existing methods solve the alignment by fitting a single surface template to each instant's 3D observations, relying on a dense point-to-point correspondence scheme, e.g. by matching individual surface points based on local geometric features...
In this paper, we present a new method to incorporate a hybrid shape prior into a level set-based active contour in order to improve its robustness to partial occlusion, clutter and noise. The proposed shape constraint is constructed in two steps. The first one consists in the alignment of the given training data according to the target shape. Then, the Hausdorff distance is used as criteria to choose...
This paper presents an enhanced version of descriptor DPM-BCF (Depth Projection Maps-based Bag of Contour Fragments). Named as eDPM, it modified the projection method by converting the depth cloud into three grayscale projected maps in three orthogonal planes. Then we extract Bag of Contour Fragments (BCF) descriptor and Histogram of Oriented Gradient (HOG) descriptor from the three grayscale projected...
Robust and accurate visual tracking is needed for many computer vision applications from video summarization to visual surveillance. Visual tracking remains to be a challenging task because of factors such as changing object appearance, illumination variations and shadows, partial and full occlusions, camera motion, distractors, and scale changes. Recently our group proposed a Likelihood of Features...
Circles detection is an important part of object recognition in image processing and computer vision. In this paper, we propose an adaptive method based on Hough transform to detect the circle shapes in digital image. The Mexican Hat filter derived from edge filter is used to concentrate the peaks of Hough local maxima. So, the circle center and its radius can be extracted easily and accurate. The...
In this paper, we focus on the control of triangular multi-agent formations with hybrid communication topology though distance-based approach. By saying hybrid topology, we mean that the communication topology contains both undirected and directed links, or in other words, the underlying graph of the formation contains both undirected and directed edges. A new type of graph, namely hybrid graph, is...
The number of devices capable of measurement Power Quality (PQ) parameters is increasing continuously in all voltage levels. Consequently, the amount of available PQ data is also growing very fast. These data contain a lot of valuable information about the behavior of PQ, but up to now it is in the most cases used only to assess compliance with limits (e.g. EN 50160 in Europe). Beside long-term characteristics...
Lung nodule segmentation is the first and the most difficult step in every Computer Aided Diagnosis (CAD). Difficulty arises due to the boring and time-consuming nature of the manual lung segmentation process. In this paper, we propose a novel automatic lung segmentation method for accurate localization of the lung nodules in computer tomography (CT) images. We present a combination of the Graph Cut...
The purpose of this paper is to present an overview of existing active contours-based object tracking methods. This restriction to recent active contours-based approaches is voluntary for two main reasons. Firstly, developed active contours models are heterogeneous that we can divide them into several sub-categories which are designed with different information and secondly, an exhaustive review of...
In this paper, we propose a novel approach to track extended objects by incorporating negative information. While traditional techniques to track extended targets use only positive measurements, assumed to stem from the target, the proposed estimator is also capable of incorporating negative measurements, which tell us where the target cannot be. To achieve this, we introduce a simple, robust, and...
In this paper, we propose a novel marker design and its tracking algorithm for room-sized MR/AR environments. The markers and the algorithm are designed to solve the following practical problems: i) the difficulties in creating and arranging markers and ii) the trade-off between inconspicuousness and robustness of markers. The proposed markers are small chips that are cut off a large paper sheet,...
We present an elegant solution to joint pre-alignment and rigid point set registration, given prior matches. Instead of performing pre-alignment and the actual registration in the separate steps, prior matches explicitly influence the registration procedure in our approach. This results in several advantages. Firstly, our approach solves the pre-alignment task — an approximate resolving of rotation...
This paper presents a novel pose-indexed based multi-view (PIMV) face alignment framework. Most of the current cascaded regression face alignment methods generally start with a mean shape. However, when the initial shape is far from the ground truth, the performance significantly deteriorates. Our approach aims to obtain a preferable initial shape from a pose-indexed shape searching space. This space...
We propose a novel multi-scale shape descriptor for shape matching and object recognition. The descriptor includes three types of invariants in multiple scales to capture discriminative local and semi-global shape features and the dynamic programming algorithm is employed for shape matching. The experimental results verify that our proposed shape feature is invariant to translation, rotation, scaling,...
This paper presents a novel local surface descriptor called rotational contour signatures (RCS) for 3D rigid objects. RCS comprises several signatures that characterize the 2D contour information derived from 3D-to-2D projection of the local surface. The inspiration of our encoding technique comes from that, viewing towards an object, its contour is an effective and robust cue for representing its...
Object recognition based on local features computed at multiple locations is robust to occlusions, strong viewpoint changes and object deformations. These features should be repeatable, precise and distinctive. We present an operator for repeatable feature detection on depth images (relative to 3D models) as well as 2D intensity images. The proposed detector is based on estimating the curviness saliency...
In this paper we propose an approach to robot grasp prioritization based on a combined arm-and-hand metric. Most traditional approaches evaluate grasps based on hand-centric metrics such as force-closure, finger spread, contact surface area and similar measures. While these are certainly important factors to predict the robustness of a grasp, they do not carry information on the feasibility of the...
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