Edge-based Approach Research Articles

Robust edge-based 3D object tracking with direction-based pose validation

In this paper we propose a robust edge-based approach for 3D textureless object tracking. We first introduce an edge-based pose estimation method, which minimizes the holistic distance between the projected object contour and the query image edges, without explicitly searching for 3D-2D correspondences. This method is accurate with a good initialization; however, it is sensitive to occlusion and fast motion, thus often gets lost in real environments. To improve robustness, we exploit consistency of edge direction for validating the correctness of the estimated 3D pose, and further incorporate the validation scheme for robust estimation, non-local searching and failure recovery. The robust estimation adopts point-wise validation to reduce the effect of outlier, resulting in a direction-based robust estimator. The non-local searching is based on particle filter, with the pose validation for a faithful weighting of particles, which is shown to be better than the distance-based weighting. The failure recovery is based on fast 2D detection, and estimates the recovered pose by searching for 3D-2D point correspondences, with the validation scheme to adaptively determine state transition. The effectiveness of our approach is demonstrated using comparative experiments on real image sequences with occlusions, large motions and background clutters.

Event-Based Control for Network Systems via Integral Quadratic Constraints

This paper investigates the event-based control for network systems. Edge-based approach is utilized to predict the value of edge state between two event instants. Different from the node-based approach, it can significantly reduce the communication burden at event instants. Based on the small gain theorem, the closed-loop system is expressed as the feedback interconnection of a linear time-invariant system and an operator. The operator describes the unstable component and has an upper bound in $L_{2}$ space and the control gain is designed, such that the feedback interconnection is stable. Furthermore, we adopt the integral quadratic constraints to describe the correlation between output and input of the operator. And the Kalman–Yakubovich–Popov Lemma is adopted to transform the infinite dimensional stability condition into one inequality. The designed event-triggering condition and distributed control law can ensure that a network system achieves synchronization. The effectiveness of the communication protocol and control strategy is illustrated by a numerical example.

Face-Centered Anisotropic Surface Impedance Boundary Conditions in FDTD

Thin-sheet models are essential to allow shielding effectiveness of composite enclosures and vehicles to be modeled. Thin dispersive sheets are often modeled using surface-impedance models in finite-difference time-domain (FDTD) codes in order to deal efficiently with the multiscale nature of the overall structure. Such boundary conditions must be applied to collocated tangential electric and magnetic fields on either side of the surface; this is usually done on the edges of the FDTD mesh cells at the electric field sampling points. However, these edge-based schemes are difficult to implement accurately on stair-cased surfaces. Here, we present a novel face-centered approach to the collocation of the fields for the application of the boundary condition. This approach naturally deals with the ambiguities in the surface normal that arise at the edges on stair-cased surfaces, allowing a simpler implementation. The accuracy of the new scheme is compared to edge-based and conformal approaches using both planar sheet and spherical shell canonical test cases. Staircasing effects are quantified and the new face-centered scheme is shown have up to 3-dB lower error than the edge-based approach in the cases considered, without the complexity and computational cost of conformal techniques.

Edge-based approach to estimate the drift of a helicopter during flight

The Institute of Flight Systems at the German Aerospace Center (DLR) site in Braunschweig Germany has set its goal into making helicopter flying as safe as possible. The new DLR research project “Rettungshubschrauber 2030” addresses the topic of aiding helicopter rescue missions. Research will be conducted to increase the safety of these missions as well as to enable the conduct of missions in circumstances where nowadays a helicopter would not be allowed to operate. One aspect of this research is to increase or maintain the situational awareness of the pilot by processing data from camera images. The paper will focus on the field of visual odometry. It examines, if an edge-based approach for extracting features is a possible alternative or addition to established feature extractors. In the paper, two algorithms for edge extraction will be compared: an algorithm that is based on Hough transform and an algorithm that is based on the Douglas–Peucker method. They are tuned for working with images of rather low resolution and are tested on their ability to detect a sufficient amount of features in camera images as well as on their computational complexity. Then, their ability to detect the drift of a helicopter is assessed using recorded data from flight tests with the advanced control technology/flying helicopter simulator (ACT/FHS) of the DLR. Their performance will be tested on the basis of reference data from the ACT/FHS which have been recorded by the use of a highly accurate INS/DGPS system. The evaluation of the algorithms yields the result that both achieve the proposed accuracy regarding the velocity estimation with the Hough-based method achieving better accuracy while taking significantly more computational time.

Texture-Independent Long-Term Tracking Using Virtual Corners.

Long-term tracking of an object, given only a single instance in an initial frame, remains an open problem. We propose a visual tracking algorithm, robust to many of the difficulties that often occur in real-world scenes. Correspondences of edge-based features are used, to overcome the reliance on the texture of the tracked object and improve invariance to lighting. Furthermore, we address long-term stability, enabling the tracker to recover from drift and to provide redetection following object disappearance or occlusion. The two-module principle is similar to the successful state-of-the-art long-term TLD tracker; however, our approach offers better performance in benchmarks and extends to cases of low-textured objects. This becomes obvious in cases of plain objects with no texture at all, where the edge-based approach proves the most beneficial. We perform several different experiments to validate the proposed method. First, results on short-term sequences show the performance of tracking challenging (low textured and/or transparent) objects that represent failure cases for competing the state-of-the-art approaches. Second, long sequences are tracked, including one of almost 30 000 frames, which, to the best of our knowledge, is the longest tracking sequence reported to date. This tests the redetection and drift resistance properties of the tracker. Finally, we report the results of the proposed tracker on the VOT Challenge 2013 and 2014 data sets as well as on the VTB1.0 benchmark, and we show relative performance of the tracker compared with its competitors. All the results are comparable with the state of the art on sequences with textured objects and superior on non-textured objects. The new annotated sequences are made publicly available.

A semi-automated method for measuring the evolution of both lumen area and blood flow in carotid from Phase Contrast MRI

Phase-Contrast (PC) velocimetry Magnetic Resonance Imaging (MRI) is a useful modality to explore cardiovascular pathologies, but requires the automatic segmentation of vessels and the measurement of both lumen area and blood flow evolutions. In this paper, we propose a semi-automated method for extracting lumen boundaries of the carotid artery and compute both lumen area and blood flow evolutions over the cardiac cycle. This method uses narrow band region-based active contours in order to correctly capture the lumen boundary without being corrupted by surrounding structures. This approach is compared to traditional edge-based active contours, considered in related works, which significantly underestimate lumen area and blood flow. Experiments are performed using both a sequence of a homemade phantom and sequences of 20 real carotids, including a comparison with manual segmentation performed by a radiologist expert. Results obtained on the phantom sequence show that the edge-based approach leads to an underestimate of carotid lumen area and related flows of respectively 18.68% and 4.95%. This appears significantly larger than weak errors obtained using the region-based approach (respectively 2.73% and 1.23%). Benefits appear even better on the real sequences. The edge-based approach leads to underestimates of 40.88% for areas and 13.39% for blood flows, compared to limited errors of 7.41% and 4.6% with our method. Experiments also illustrate the high variability and therefore the lack of reliability of manual segmentation.

Road intersection detection and classification using hierarchical SVM classifier

In this paper, a hierarchical multi-classification approach using support vector machines (SVM) has been proposed for road intersection detection and classification. Our method has two main steps. The first involves the road detection. For this purpose, an edge-based approach has been developed using the bird’s eye view image which is mapped from the perspective view of the road scene. Then, the concept of vertical spoke has been introduced for road boundary form extraction. The second step deals with the problem of road intersection detection and classification. It consists on building a hierarchical SVM classifier of the extracted road forms using the unbalanced decision tree architecture. Many measures are incorporated for good evaluation of the proposed solution. The obtained results are compared to those of Choi et al. (2007).

A New Edge-Based Method for Artificial Text Detection

In video indexing and retrieval systems, textual information is high-level semantic content to describe images or video frames, which is also one of the most interesting objects of study. A great progress has been made in text detection in recent decades, but it is still a great challenge due to the complex background, various fonts and different languages, etc. In this paper, we propose a edge-based approach to detect artificial text. First, the image edge map and difference range map are calculated. Then the map is binarized by local threshold method. Finally the textual information is located through the regional projection analysis. Experience results show our method’s precision rate is 91.1% and recall rate 93.2%, which outperforms the previous work.

의미간의 유사도 연구의 패러다임 변화의 필요성-인지 의미론적 관점에서의 고찰

Semantic similarity/relatedness measure between two concepts plays an important role in research on system integration and database integration. Moreover, current research on keyword recommendation or tag clustering strongly depends on this kind of semantic measure. For this reason, many researchers in various fields including computer science and computational linguistics have tried to improve methods to calculating semantic similarity/relatedness measure. This study of similarity between concepts is meant to discover how a computational process can model the action of a human to determine the relationship between two concepts. Most research on calculating semantic similarity usually uses ready-made reference knowledge such as semantic network and dictionary to measure concept similarity. The topological method is used to calculated relatedness or similarity between concepts based on various forms of a semantic network including a hierarchical taxonomy. This approach assumes that the semantic network reflects the human knowledge well. The nodes in a network represent concepts, and way to measure the conceptual similarity between two nodes are also regarded as ways to determine the conceptual similarity of two words(i.e,. two nodes in a network). Topological method can be categorized as node-based or edge-based, which are also called the information content approach and the conceptual distance approach, respectively. The node-based approach is used to calculate similarity between concepts based on how much information the two concepts share in terms of a semantic network or taxonomy while edge-based approach estimates the distance between the nodes that correspond to the concepts being compared. Both of two approaches have assumed that the semantic network is static. That means topological approach has not considered the change of semantic relation between concepts in semantic network. However, as information communication technologies make advantage in sharing knowledge among people, semantic relation between concepts in semantic network may change. To explain the change in semantic relation, we adopt the cognitive semantics. The basic assumption of cognitive semantics is that humans judge the semantic relation based on their cognition and understanding of concepts. This cognition and understanding is called `World Knowledge.` World knowledge can be categorized as personal knowledge and cultural knowledge. Personal knowledge means the knowledge from personal experience. Everyone can have different Personal Knowledge of same concept. Cultural Knowledge is the knowledge shared by people who are living in the same culture or using the same language. People in the same culture have common understanding of specific concepts. Cultural knowledge can be the starting point of discussion about the change of semantic relation. If the culture shared by people changes for some reasons, the human`s cultural knowledge may also change. Today`s society and culture are changing at a past face, and the change of cultural knowledge is not negligible issues in the research on semantic relationship between concepts. In this paper, we propose the future directions of research on semantic similarity. In other words, we discuss that how the research on semantic similarity can reflect the change of semantic relation caused by the change of cultural knowledge. We suggest three direction of future research on semantic similarity. First, the research should include the versioning and update methodology for semantic network. Second, semantic network which is dynamically generated can be used for the calculation of semantic similarity between concepts. If the researcher can develop the methodology to extract the semantic network from given knowledge base in real time, this approach can solve many problems related to the change of semantic relation. Third, the statistical approach based on corpus analysis can be an alternative for the method using semantic network. We believe that these proposed research direction can be the milestone of the research on semantic relation.

Storing and querying fuzzy XML data in relational databases

Information imprecision and uncertainty exist in many real-world applications and for this reason fuzzy data management has been extensively investigated in various database management systems. Currently, introducing native support for XML data in relational database management systems (RDBMs) has attracted considerable interest with a view to leveraging the powerful and reliable data management services provided by RDBMs. Although there is a rich literature on XML-to-relational storage, none of the existing solutions satisfactorily addresses the problem of storing fuzzy XML data in RDBMs. In this paper, we study the methodology of storing and querying fuzzy XML data in relational databases. In particular, we present an edge-based approach to shred fuzzy XML data into relational data. The unique feature of our approach is that no schema information is required for our data storage. On this basis, we present a generic approach to translate path expression queries into SQL for processing XML queries.

EDGE-BASED REGISTRATION FOR AIRBORNE IMAGERY AND LIDAR DATA

Abstract. Aerial imagery and LIDAR points are two important data sources for building reconstruction in a geospatial area. Aerial imagery implies building contours with planimetric features; LIDAR data explicitly represent building geometries using three-dimensional discrete point clouds. Data integration may take advantage of merits from two data sources in building reconstruction and change detection. However, heterogeneous data may contain a relative displacement because of different sensors and the capture time. To reduce this displacement, data registration should be an essential step. Therefore, this investigation proposes an edge-based approach to register these two data sets in three parts: (1) data preprocessing; (2) feature detection; and (3) data registration. The first step rasterizes laser point clouds into a pseudo-grid digital surface model (PDSM), which describes the relief with the original elevation information. The second step implements topological analyses to detect image edges and three-dimensional structure lines from the aerial image and PDSM. These detected features provide the initial positions of building shapes for registration. The third part registers these two data sets in Hough space to compensate for the displacement. Because each building may have prominent geometric structures, the proposed scheme transforms these two groups of edges, and estimates the correspondence by the Hough distribution. The following procedure then iteratively compares two groups of Hough patterns, which are from an aerial image and LIDAR data. This iterative procedure stops when the displacement is within a threshold. The test area is located in Taipei City, Taiwan. DMC system captured the aerial image with 18-cm spatial resolution. The LIDAR data were scanned with a 10-point density per square meter using the Leica ALS50 system. This study proposed a 50 cm spatial resolution of PDSM, which is slightly larger than the point spacing. The experiment selected two buildings to evaluate the performance of the proposed scheme. The manually edited building boundaries from the stereo aerial images are the reference data for validation. Comparisons indicated that the registration procedure could adjust the displacement within 50 cm, which relates to PDSM resolution. These preliminary results also demonstrated the possibility of providing locations for building reconstruction.

Estimation of Word Net-Based Lexical Semantic Similarity Measure for Telugu Documents

The estimation of lexical semantic relatedness has numerous applications in NLP. Several measures are available for the evaluation of lexical semantic relatedness. This paper presents two approaches for measuring semantic similarity/distance between words and concepts with the help of WordNet-Telugu. The edge-based approach of the edge counting scheme and the node-based approach of the information content calculation have been explored. In the field of concepts, the measure of Wu and Palmer has the advantage of being simple to implement and have good performances compared to the other similarity measures. The obtained results show that the Wu and Palmer approach presents a better performance in terms of relevance.

Authorship Detection and Encoding for eBay Images

This paper describes a framework to detect authorship of eBay images. It contains three modules: editing style summarization, classification and multi-account linking detection. For editing style summarization, three approaches, namely the edge-based approach, the color-based approach, and the color probability approach, are proposed to encode the common patterns inside a group of images with similar editing styles into common edge or color models. Prior to the summarization step, an edge-based clustering algorithm is developed. Corresponding to the three summarization approaches, three classification methods are developed accordingly to predict the authorship of an unlabeled test image. For multi-account linking detection, to detect the hidden owner behind multiple eBay seller accounts, two methods to measure the similarity between seller accounts based on similar models are presented.

An edge-based approach to the alignment of syntactic phases and prosodic phrases1

In phase-based syntax, syntactic structure is sent in chunks – spell-out domain by spell-out domain – for phonological interpretation. The spell-out domain of an embedded clause would, then, form a separate phonological domain from its matrix. In this paper, I test this theory on the prosodic phrasing of relative clauses in some Bantu languages, and show that the phrasing contradicts the proposal that embedded spell-out domains necessarily form distinct prosodic domains. Instead, the phrasing is most consistent with a non-cyclic Edge-based analysis, in which only one edge of a syntactic phase constituent is aligned with the edge of a prosodic phrase.

Automated Polar Ice Thickness Estimation From Radar Imagery

This paper focuses on automating the task of estimating Polar ice thickness from airborne radar data acquired over Greenland and Antarctica. This process involves the identification and accurate selection of the ice sheet's surface location and interface between the ice sheet and the underlying bedrock for each measurement. Identifying the surface and bedrock locations in the radar imagery enables the computation of ice sheet thickness, which is important for the study of ice sheets, their volume, and how they may contribute to global climate change. The time-consuming manual approach requires sparse hand-selection of surface and bedrock interfaces by several human experts, and interpolating between the selections to save time. Two primary methods have been studied in this paper, namely, edge-based and active contour. Results are evaluated and presented using the metrics of time requirements and accuracy. Automated ice thickness estimation results from 2006 and 2007 Greenland field campaigns illustrate that the edge-based approach offers faster processing (seconds compared to minutes), but suffers from a lack of continuity and smoothness aspects that active contours provide. The active contour approach is more accurate when compared to ground truth selections provided by human experts, and has proven to be more robust to image artifacts. It is shown that both techniques offer advantages which could be integrated to yield a more effective system.

Adaptive Edge-Oriented Shot Boundary Detection

We study the problem of video shot boundary detection using an adaptive edge-oriented framework. Our approach is distinct in its use of multiple multilevel features in the required processing. Adaptation is provided by a careful analysis of these multilevel features, based on shot variability. We consider three levels of adaptation: at the feature extraction stage using locally-adaptive edge maps, at the video sequence level, and at the individual shot level. We show how to provide adaptive parameters for the multilevel edge-based approach, and how to determine adaptive thresholds for the shot boundaries based on the characteristics of the particular shot being indexed. The result is a fast adaptive scheme that provides a slightly better performance in terms of robustness, and a five fold efficiency improvement in shot characterization and classification. The reported work has applications beyond direct video indexing, and could be used in real-time applications, such as in dynamic monitoring and modeling of video data traffic in multimedia communications, and in real-time video surveillance. Experimental results are included.

Exploiting edge capability for wireless sensor networking

As considerable progress is being made in wireless sensor networking, it is envisioned that sensor nodes will be on the cubic millimeter scale, posing stringent constraints on the processing, communication, and storage capabilities of sensor nodes. While it is important to continue pursuing novel algorithms and protocols to squeeze the most out of the existing design space (sensor nodes), it is equally important to explore a new design paradigm for future sensor networks to reduce the complexity burden on sensor nodes. We propose to exploit capabilities at the network edge (i.e., an edge-based approach). We overview existing approaches to this end and present a novel edge-based routing protocol, called BeamStar, as a case study. We show that exploiting edge capability provides a new dimension of freedom for wireless sensor networking, and is effective in relieving the processing, communication, and storage requirements of sensor nodes.

Mumford–Shah based registration: a comparison of a level set and a phase field approach

Traditionally, different image processing tasks are mainly considered on their own. The main aim of this paper is a combination of registration, i.e., the spatial alignment of images and egmentation, i.e., the recognition of edges and object contours in images. A proper registration depends on a good initial segmentation and vice versa. In this paper, it is proposed to link these problems together by formulating a coupled variational problem. We will focus on an edge-based approach instead of considering image intensities and propose a variational formulation based on the Mumford–Shah free discontinuity problem. This paper is particularly devoted to a comparison of a sharp interface approach with the phase field analogue.

BeamStar: An Edge-Based Approach to Routing in Wireless Sensor Networks

Current expectations on sensor node in terms of size, cost, and energy efficiency have led to a severely limited design space on hardware and software. In this paper, we explore capabilities at the network edge for sensor networks, aiming to reduce the hardware and software complexity of a sensor node without sacrificing network performance. We present a novel edge-based routing protocol, nicknamed BeamStar, for wireless sensor networks. Under BeamStar, the base station exploits some nice properties associated with directional antenna and power control at the base station. We devise a simple protocol so that each sensor node can determine its location information passively with minimum control overhead. We also show how to design a robust routing protocol based on the location information at each sensor node. Under the proposed protocol, sensor nodes are relieved of the activities (or burdens) that are associated with control and routing, thus enabling much simpler hardware and software implementation at sensor nodes. Simulation results demonstrate that BeamStar achieves high reliability at comparable energy consumptions as compared with prior work. It is a viable approach to pursue size and cost reduction for future sensor node design.

Increasing resolution of digital images using edge-based approach

AbstractThis paper presents the results of our research aimed at obtaining new methods for increasing resolution of digital images giving better visual results. Classification of these methods and implementation of some algorithms is also shortly presented here. The main part of the paper presents modification and development of the new methods. Main new feature, which we added to the interpolation algorithms, consists in taking into consideration in the final image (i.e., after interpolation at high resolution) the edges detected in the original image (i.e., before interpolation). Summing an image and its properly processed edges in the interpolation process enables us to get final image characterized by better sharpness with simultaneous precise presentation of the image details interpolated to higher resolution.