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Visual place recognition (VPR) in changing environments is an urgent challenge for long-term autonomous navigation. One recent ConvNet landmark-based approach exploits region landmarks coupled with ConvNet features to match images, and the approach has shown promising results under significant environmental and viewpoint changes. In this paper, we propose a robust ConvNet landmark-based system for...
Illumination changes are a typical problem for many outdoor long-term applications such as visual place recognition. Keypoints may fail to match between images taken at the same location but different times of the day. Although recently some methods are presented for creating shadow-free image representations, all of them have the limitation in terms of dealing with night images and non-Planckian...
Deep convolutional neural networks (CNN) have recently been shown in many computer vision and pattern recognition applications to outperform by a significant margin state-of-the-art solutions that use traditional hand-crafted features. However, this impressive performance is yet to be fully exploited in robotics. In this paper, we focus one specific problem that can benefit from the recent development...
A simple and reliable keypoint matching method is proposed in this paper. Our research is motivated by the desire to improve the performance of multi-view geometry (MVG) based verification in visual loop closure detection under significant illumination change, where traditional methods may fail due to their inability to either find a sufficient number of correctly matched keypoints or identify correct...
In order to estimate the amount of oil that can be recovered from oil sands slurry, technically referred to as processability number, we propose a method based on image processing in this paper. Our study begins with a review of human observations in conducting this task to determine visual features pertinent for assessing ore slurry quality. Subsequently we extract potentially useful image features...
In this paper, we present a novel approach for visual loop-closure detection in autonomous robot navigation. Our method uses locality sensitive hashing (LSH) as the basic technique for matching the binary visual features in the current view of a robot with the visual features in the robot appearance map. We show that this approach is highly efficient in comparison with using non-binary visual features...
An important problem in robot simultaneous localization and mapping (SLAM) is loop closure detection. Recent studies of the problem have led to successful development of methods that are based on images captured by the robot. These methods tackle the issue of efficiency through data structures such as indexing and hierarchical (tree) organization of the image data that represent the robot map. In...
Vector-quantization can be a computationally expensive step in visual bag-of-words (BoW) search when the vocabulary is large. A BoW-based appearance SLAM needs to tackle this problem for an efficient real-time operation. We propose an effective method to speed up the vector quantization process in BoW-based visual SLAM. We employ a graph-based nearest neighbor search (GNNS) algorithm to this aim,...
Learning and then recognizing a path is a challenging task for state of the art algorithms in computer vision and robotics. In this paper, we present a new approach to visual localization along a path. Classically visual paths have been described using keyframes, single images taken at specific locations. Our method uses all the images of a path segment, Gabor-Gist and, principal component analysis...
We propose a method for egomotion estimation from images obtained by a pair of stereo cameras for the reconstruction of 3D scene. The proposed method improves feature matching by using two eliminating criteria to filter out unlikely matching points and restricts the search window according to the epipolar constraint. The method also improves calculated motion by using bundle adjustment to integrate...
We present the performance evaluation of different whole-image descriptors in visual loop closure detection. A whole-image descriptor here is defined as the one that does not require keypoint detection and is therefore fast to extract. In addition, it can be extremely compact to reduce storage requirement. This type of image descriptors are attracting an increasing amount of interest in appearance-based...
The development of smart grid has proposed higher request to the intelligent dispatching in power construction. To meet these requirements, in the basis of the full research on dispatchers' actual habits, this paper proposed the use of the existing power grid analysis theory to establish power grid running status indicators and the novel hierarchical display frame design, which combines with visualization...
In this paper, we present a method for visual loop closure detection using a compact image descriptor, Gabor-Gist. In contrast to the Bag-of-Words (BoW) approach, which is dominant in recent studies of the loop closure detection problem that derives an image descriptor from locally extracted keypoint descriptors, our method relies on a single efficient image descriptor of low dimension to describe...
This paper investigates the problem of robot visual homing — the navigation to a goal location by a mobile robot using visual sensory input. The visual homing approach taken is to consider the flow vectors between a robot's current view and a desired milestone view. The flow vectors can be used to determine an angular velocity command that attempts to align the two views under a constant forward speed...
We propose a simple and effective method for visual loop closure detection in appearance-based robot SLAM. Unlike the Bag-of-Words (BoW hereafter) approach in most existing work of the problem, our method uses direct feature matching to detect loop closures and therefore avoid the perceptual aliasing problem caused by the vector quantization process of BoW. We show that a tree structure can be efficient...
In this work we present a new approach for detecting loop closures in a real-time online setting. The Loop Closure Detection problem is important in visual SLAM applications and different approaches exist to deal with this problem. Most of these approaches are based on the Bag-of-Words approach, and assume a fixed visual vocabulary can work in different types of environments. However BOW is known...
In this paper, we present a novel method for visual loop-closure detection in autonomous robot navigation. Our method, which we refer to as bag-of-raw-features or BoRF, uses scale-invariant visual features (such as SIFT) directly, rather than their vector-quantized representation or bag-of-words (BoW), which is popular in recent studies of the problem. BoRF avoids the offline process of vocabulary...
Vast marine area possesses over 3/4 of the global surface, where human activities occur more and more. Over 90% of imported crude oil in China is transported by oil tankers, which comprise the main part of vessel fleets in the China seas. Fishery is another human activity in the oceans, which is related to resource management and EEZ protection. Both maritime traffic and fishery law enforcement need...
Up to now, 3D watermarking has mainly focused on triangle meshes which are the most used digital representations of the shape of a 3D model. In this paper, we present a watermarking technique for authentication of 3D polygonal meshes. We propose a robust 3D watermarking method for high rate embedding of a watermark into 3D polygonal meshes. The proposed technique is based on spectral mesh compression,...
This paper is concerned with the problem of keyframe detection in appearance-based visual SLAM. Appearance SLAM models a robot's environment topologically by a graph whose nodes represent strategically interesting places that have been visited by the robot and whose arcs represent spatial connectivity between these places. Specifically, we discuss and compare various methods for identifying the next...
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