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An RGB-D camera is a sensor which outputs range and color information about objects. Recent technological advances in this area have introduced affordable RGB-D devices in the robotics community. In this paper, we present a real-time technique for 6-DoF camera pose estimation through the incremental registration of RGB-D images. First, a set of edge features are computed from the depth and color images...
In order to obtain the application of three dimensional (3D) reconstruction techniques for disaster visualization system on the mountain. This research is to develop a 3D model of mountain from triple images, and try to develop real time reconstruction process of 3D-mountain. The processes of this research study consist of seven stages to develop the 3D model's mountain surface. In feature points...
Simultaneous Localization and Mapping (SLAM) is a fundamental problem in the mobile robotics. As SLAM is usually utilized in an indoor environment, we select the ceiling view (CV) as a stable source of features. In this research, three types of features are extracted from CV and constitute a single map. The landmarks detected from ceilings are ceiling boundaries, electric lamps, and circles. Each...
The accuracy and robustness of SLAM critically depend on the properties of feature points. This paper presents a robust corner detection method suitable for indoor mobile robot navigation. We combine the advantages of edge-based corner detection and intensity-based corner detection. Orientation field estimation followed by image-based curvature estimation can detect corners stably and accurately....
This paper presents a vision-based vehicle detection system in the infrared (IR) and vision system using an effective feature extraction and algorithm. This system follows two steps: Hypothesis Generation (HG) method and Hypothesis Verification (HV) method. In HG method, vertical and horizontal edges are used. To extract these edges effectively a neighborhood gradient prediction(NGP) edge detection...
This paper proposes a rear vision camera-based vehicle detection system which could detect if any rear vehicle exists in ego lane and if any vehicles in adjacent lanes are overtaking. The source image is firstly applied with distortion calibration which helps the following Hough transform to detect the existence of lane lines. The rear vehicle in ego lane is detected by a combination of feature-based...
In this paper, we propose a vision-based robust vehicle detection and inter-vehicle distance estimation algorithm for driving assistance system. It uses the directional edge features, as well as the Haar-like features of car rear-shadows for detection of front vehicles. The use of additional vehicle edge features greatly reduces the false-positive errors. And, after analyzing two inter-vehicle distance...
In this paper we present an algorithm to detect text on video frames consisting of lecture slides. We begin by performing a multi-channel wavelet transform and then merge the channel components for the high frequency sub bands to obtain a composite energy map. Thresholding the energy map results in an edge map consisting of candidate text pixels — some of these correspond to actual text and others...
Recently, many types of cameras have come into use around the world. Because of this, color correction has become a significant problem and color charts have been developed for evaluation and correction purposes. In this paper, a method for detecting color charts of arbitrary size, rotation and location from camera images is proposed for color correction purposes. This method combines several hierarchical...
Point-based targets, such as checkerboards, are often not practical for outdoor camera calibration, as cameras are usually at significant heights requiring extremely large calibration patterns on the ground. Fortunately, it is possible to make use of existing non-point landmarks in the scene by formulating camera calibration in terms of image alignment. In this paper, we simultaneously estimate the...
Multioriented text detection in video frames is not as easy as detection of captions or graphics or overlaid texts, which usually appears in the horizontal direction and has high contrast compared to its background. Multioriented text generally refers to scene text that makes text detection more challenging and interesting due to unfavorable characteristics of scene text. Therefore, conventional text...
We present a novel algorithm that takes as input an uncalibrated unordered set of spherical panoramic images and outputs their relative pose up to a global scale. The panoramas contain both indoor and outdoor shots and each set was taken in a particular indoor location e.g. a bakery or a restaurant. The estimated pose is used to build a map of the location, and allow easy visual navigation and exploration...
Lane detection plays an important role in vision based intelligent vehicle systems. A new lane detection method based on lane mark segment features and general a priori knowledge is proposed in this paper. Instead of detecting each feature point separately from limited local view, a lane mark segment detection method is designed for detecting each lane mark segment on the whole. Some a priori knowledge...
Local image feature extractors that select local maxima of the determinant of Hessian function have been shown to perform well and are widely used. This paper introduces the negative local minima of the determinant of Hessian function for local feature extraction. The properties and scale-space behaviour of these features are examined and found to be desirable for feature extraction. It is shown how...
An innovative approach for on-road real-time preceding vehicle detection system is presented in this paper. Vehicle detection is performed by using knowledge based candidate generation followed by appearance based verification. The primary shadow present underneath the vehicle chassis i.e. self shadow is used to generate candidate regions in the image. The use of only self shadow provides improved...
This paper addresses the problem of automatically aligning historical architectural paintings with 3D models obtained using multi-view stereo technology from modern photographs. This is a challenging task because of the variations in appearance, geometry, color and texture due to environmental changes over time, the non-photorealistic nature of architectural paintings, and differences in the viewpoints...
Computer vision algorithms for pedestrian detection are often based on classification derived from supervised learning and therefore require training data, which can be built by using generic or specific images. In this field, INRIA datasets are a standard reference but include only few CCTV camera samples. Therefore, for a CCTV camera system it might be interesting to have specific training data...
We introduce a new approach to reconstructing accurate camera geometry and 3D models for urban structures in a holistic fashion, i.e., without relying on extraction or matching of traditional local features such as points and edges. Instead, we use semi-global or global features based on transform invariant low-rank textures, which are ubiquitous in urban scenes. Modern high-dimensional optimization...
In this paper we explore how a structured light depth sensor, in the form of the Microsoft Kinect, can assist with indoor scene segmentation. We use a CRF-based model to evaluate a range of different representations for depth information and propose a novel prior on 3D location. We introduce a new and challenging indoor scene dataset, complete with accurate depth maps and dense label coverage. Evaluating...
This paper proposes a new real-time Augmented Reality based tool to help in disassembly for maintenance operations. This tool provides workers with augmented instructions to perform maintenance tasks more efficiently. Our prototype is a complete framework characterized by its capability to automatically generate all the necessary data from input based on untextured 3D triangle meshes, without requiring...
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