scholarly journals Crater Detection and Recognition Method for Pose Estimation

2021 ◽  
Vol 13 (17) ◽  
pp. 3467
Author(s):  
Zihao Chen ◽  
Jie Jiang
Keyword(s):  
Pose Estimation ◽  
Graph Matching ◽  
Recognition Algorithm ◽  
Matching Problem ◽  
Crater Detection ◽  
Weighted Bipartite Graph ◽  
Dense Point ◽  
Stage 1 ◽  
Two Stages ◽  
Detection And Recognition

A crater detection and recognition algorithm is the key to pose estimation based on craters. Due to the changing viewing angle and varying height, the crater is imaged as an ellipse and the scale changes in the landing camera. In this paper, a robust and efficient crater detection and recognition algorithm for fusing the information of sequence images for pose estimation is designed, which can be used in both flying in orbit around and landing phases. Our method consists of two stages: stage 1 for crater detection and stage 2 for crater recognition. In stage 1, a single-stage network with dense anchor points (dense point crater detection network, DPCDN) is conducive to dealing with multi-scale craters, especially small and dense crater scenes. The fast feature-extraction layer (FEL) of the network improves detection speed and reduces network parameters without losing accuracy. We comprehensively evaluate this method and present state-of-art detection performance on a Mars crater dataset. In stage 2, taking the encoded features and intersection over union (IOU) of craters as weights, we solve the weighted bipartite graph matching problem, which is matching craters in the image with the previously identified craters and the pre-established craters database. The former is called “frame-frame match,” or FFM, and the latter is called “frame-database match”, or FDM. Combining the FFM with FDM, the recognition speed is enabled to achieve real-time on the CPU (25 FPS) and the average recognition precision is 98.5%. Finally, the recognition result is used to estimate the pose using the perspective-n-point (PnP) algorithm and results show that the root mean square error (RMSE) of trajectories is less than 10 m and the angle error is less than 1.5 degrees.

scholarly journals FPGA Implementation of Reconfigurable Finite State Machine with Input Multiplexing Architecture Using Hungarian Method

2018 ◽  
Vol 2018 ◽  
pp. 1-15 ◽  
Author(s):  
Nitish Das ◽  
P. Aruna Priya
Keyword(s):  
Finite State Machine ◽  
Graph Matching ◽  
Digital Signal ◽  
State Machine ◽  
Fpga Implementation ◽  
Greedy Heuristic ◽  
Matching Problem ◽  
Input Selection ◽  
Weighted Bipartite Graph ◽  
Finite State

The mathematical model for designing a complex digital system is a finite state machine (FSM). Applications such as digital signal processing (DSP) and built-in self-test (BIST) require specific operations to be performed only in the particular instances. Hence, the optimal synthesis of such systems requires a reconfigurable FSM. The objective of this paper is to create a framework for a reconfigurable FSM with input multiplexing and state-based input selection (Reconfigurable FSMIM-S) architecture. The Reconfigurable FSMIM-S architecture is constructed by combining the conventional FSMIM-S architecture and an optimized multiplexer bank (which defines the mode of operation). For this, the descriptions of a set of FSMs are taken for a particular application. The problem of obtaining the required optimized multiplexer bank is transformed into a weighted bipartite graph matching problem where the objective is to iteratively match the description of FSMs in the set with minimal cost. As a solution, an iterative greedy heuristic based Hungarian algorithm is proposed. The experimental results from MCNC FSM benchmarks demonstrate a significant speed improvement by 30.43% as compared with variation-based reconfigurable multiplexer bank (VRMUX) and by 9.14% in comparison with combination-based reconfigurable multiplexer bank (CRMUX) during field programmable gate array (FPGA) implementation.

scholarly journals A Novel Metric-Learning-Based Method for Multi-Instance Textureless Objects’ 6D Pose Estimation

2021 ◽  
Vol 11 (22) ◽  
pp. 10531
Author(s):  
Chenrui Wu ◽  
Long Chen ◽  
Shiqing Wu
Keyword(s):  
Pose Estimation ◽  
Real World ◽  
Graph Matching ◽  
Metric Learning ◽  
Intelligent Manufacturing ◽  
Fixed Size ◽  
Industrial Environment ◽  
Real World Applications ◽  
Dense Point ◽  
Detection Stage

6D pose estimation of objects is essential for intelligent manufacturing. Current methods mainly place emphasis on the single object’s pose estimation, which limit its use in real-world applications. In this paper, we propose a multi-instance framework of 6D pose estimation for textureless objects in an industrial environment. We use a two-stage pipeline for this purpose. In the detection stage, EfficientDet is used to detect target instances from the image. In the pose estimation stage, the cropped images are first interpolated into a fixed size, then fed into a pseudo-siamese graph matching network to calculate dense point correspondences. A modified circle loss is defined to measure the differences of positive and negative correspondences. Experiments on the antenna support demonstrate the effectiveness and advantages of our proposed method.

scholarly journals Reducing Invertible Embedding Distortion Using Graph Matching Model

2020 ◽  
Vol 2020 (4) ◽  
pp. 21-1-21-10
Author(s):  
Hanzhou Wu ◽  
Xinpeng Zhang
Keyword(s):  
Bipartite Graph ◽  
Graph Matching ◽  
Minimum Weight ◽  
Rate Distortion ◽  
Maximum Matching ◽  
Rate Distortion Optimization ◽  
Matching Model ◽  
Matching Problem ◽  
Weighted Bipartite Graph ◽  
Embedding Distortion

Invertible embedding allows the original cover and embedded data to be perfectly reconstructed. Conventional methods use a well-designed predictor and fully exploit the carrier characteristics. Due to the diversity, it is actually hard to accurately model arbitrary covers, which limits the practical use of methods relying heavily on content characteristics. It has motivated us to revisit invertible embedding operations and propose a general graph matching model to generalize them and further reduce the embedding distortion. In the model, the rate-distortion optimization task of invertible embedding is derived as a weighted bipartite graph matching problem. In the bipartite graph, the nodes represent the values of cover elements, and the edges indicate the candidate modifications. Each edge is associated with a weight indicating the corresponding embedding distortion for the connected nodes. By solving the minimum weight maximum matching problem, we can find the optimal embedding strategy under the constraint. Since the proposed work is a general model, it can be incorporated into existing works to improve their performance, or used for designing new invertible embedding systems. We incorporate the proposed work into a part of state-of-the-arts, and experiments show that it significantly improves the rate-distortion performance. To the best knowledge of the authors, it is probably the first work studying rate-distortion optimization of invertible embedding from the perspective of graph matching model.

scholarly journals Large-scale Semantic Parsing without Question-Answer Pairs

2014 ◽  
Vol 2 ◽  
pp. 377-392 ◽  
Author(s):  
Siva Reddy ◽  
Mirella Lapata ◽  
Mark Steedman
Keyword(s):  
Natural Language ◽  
Large Scale ◽  
Graph Matching ◽  
State Of The Art ◽  
The State ◽  
Semantic Parsing ◽  
Matching Problem ◽  
Weak Supervision ◽  
Benchmark Datasets

In this paper we introduce a novel semantic parsing approach to query Freebase in natural language without requiring manual annotations or question-answer pairs. Our key insight is to represent natural language via semantic graphs whose topology shares many commonalities with Freebase. Given this representation, we conceptualize semantic parsing as a graph matching problem. Our model converts sentences to semantic graphs using CCG and subsequently grounds them to Freebase guided by denotations as a form of weak supervision. Evaluation experiments on a subset of the Free917 and WebQuestions benchmark datasets show our semantic parser improves over the state of the art.

scholarly journals Effect of 2CaO·SiO2 particles addition on dephosphorization behavior

2020 ◽  
Vol 39 (1) ◽  
pp. 219-227
Author(s):  
Aijun Deng ◽  
Yunjin Xia ◽  
Jie Li ◽  
Dingdong Fan
Keyword(s):  
Liquid Slag ◽  
Solid Phase ◽  
Solid Particles ◽  
Hot Metal ◽  
Liquid Silicate ◽  
Phase Complex ◽  
Dephosphorization Slag ◽  
Stage 1 ◽  
Two Stages ◽  
Complex Liquid

AbstractThe effect of the addition of 2CaO·SiO2 solid particles on dephosphorization behavior in carbon-saturated hot metal was investigated. The research results showed that the addition of 2CaO·SiO2 particles have little influence on desilication and demanganization, and the removal of [Si] and [Mn] occurred in the first 5 min with different conditions where the contents of 2CaO·SiO2 particles addition for the conditions 1, 2, 3, 4, and 5 are 0, 2.2, 6.4, 8.6, and 13.0 g, respectively. The final dephosphorization ratios for the conditions 1, 2, 3, 4, and 5 are 61.2%, 66.9%, 79.6%, 63.0%, and 78.1%, respectively. The dephosphorization ratio decreases with the increase of 2CaO·SiO2 particles in the first 3 min. The reason for this is that the dephosphorization process between hot metal and slag containing C2S phase consisted of two stages: Stage 1, [P] transfers from hot metal to liquid slag and Stage 2, the dephosphorization production (3CaO·P2O5) in liquid slag reacts with 2CaO·SiO2 to form C2S–C3P solid solution. The increase of 2CaO·SiO2 particles increases the viscosity of slag and weakens the dephosphorization ability of the stage 1. The SEM and XRD analyses show that the phase of dephosphorization slag with the addition of different 2CaO·SiO2 particles is composed of white RO phase, complex liquid silicate phase, and black solid phase (C2S or C2S–C3P). Because the contents of C2S–C3P and 2CaO·SiO2 in slag and the dephosphorization ability of the two stages are different, the dephosphorization ability with different conditions is different.

scholarly journals Archaeological studies In theIlmeny state reserve, South Urals

2020 ◽  
pp. 112-122
Author(s):  
V.S. Mosin
Keyword(s):  
Bronze Age ◽  
Iron Age ◽  
Early Iron Age ◽  
South Urals ◽  
Stone Age ◽  
Stage 1 ◽  
Two Stages

The paper describes two stages of archeological studies at the territory of the Ilmeny State Reserve. Stage 1 is related to expedition of L.Ya. Krizhevskaya in 1961–1970, which resulted in fn-ding of more than 40 settlements and sites of the Stone Age, Bronze Age and Early Iron Age. Seven settlements were excavated. Stage 2 studies began in 2010 and are continued at present. These works allowed us to fnd about 40 sites and settlements of the Stone Age and to excavate of the Stone Age sites and Bronze Ages burials.

scholarly journals Three-Dimensional Graph Matching to Identify Secondary Structure Correspondence of Medium-Resolution Cryo-EM Density Maps

Biomolecules ◽  
2021 ◽  
Vol 11 (12) ◽  
pp. 1773
Author(s):  
Bahareh Behkamal ◽  
Mahmoud Naghibzadeh ◽  
Mohammad Reza Saberi ◽  
Zeinab Amiri Tehranizadeh ◽  
Andrea Pagnani ◽  
...  
Keyword(s):  
Secondary Structure ◽  
Graph Matching ◽  
Protein Complexes ◽  
Three Dimensional ◽  
Protein Structure Determination ◽  
Secondary Structures ◽  
Computational Method ◽  
Target Sequence ◽  
Matching Problem ◽  
Medium Resolution

Cryo-electron microscopy (cryo-EM) is a structural technique that has played a significant role in protein structure determination in recent years. Compared to the traditional methods of X-ray crystallography and NMR spectroscopy, cryo-EM is capable of producing images of much larger protein complexes. However, cryo-EM reconstructions are limited to medium-resolution (~4–10 Å) for some cases. At this resolution range, a cryo-EM density map can hardly be used to directly determine the structure of proteins at atomic level resolutions, or even at their amino acid residue backbones. At such a resolution, only the position and orientation of secondary structure elements (SSEs) such as α-helices and β-sheets are observable. Consequently, finding the mapping of the secondary structures of the modeled structure (SSEs-A) to the cryo-EM map (SSEs-C) is one of the primary concerns in cryo-EM modeling. To address this issue, this study proposes a novel automatic computational method to identify SSEs correspondence in three-dimensional (3D) space. Initially, through a modeling of the target sequence with the aid of extracting highly reliable features from a generated 3D model and map, the SSEs matching problem is formulated as a 3D vector matching problem. Afterward, the 3D vector matching problem is transformed into a 3D graph matching problem. Finally, a similarity-based voting algorithm combined with the principle of least conflict (PLC) concept is developed to obtain the SSEs correspondence. To evaluate the accuracy of the method, a testing set of 25 experimental and simulated maps with a maximum of 65 SSEs is selected. Comparative studies are also conducted to demonstrate the superiority of the proposed method over some state-of-the-art techniques. The results demonstrate that the method is efficient, robust, and works well in the presence of errors in the predicted secondary structures of the cryo-EM images.

scholarly journals Matching-based cache placement decision for 5G network caching

2021 ◽  
Author(s):  
Shadi Sadeghpour Kharkan
Keyword(s):  
Graph Matching ◽  
Placement Problem ◽  
Matching Problem ◽  
Matching Algorithm ◽  
Cell Network ◽  
5G Network ◽  
Backhaul Link ◽  
Random Placement ◽  
Cache Placement ◽  
Bottleneck Link

In this thesis, we present a cache placement scheme to deal with backhaul link constraint in Small Cell Network for 5G wireless network. We formulated the cache placement problem as a graph matching problem and presented an optimal file-helper matching algorithm. We defined stability criterion for the matching and found that our matching solution is stable in the sense that every helper finds at least one file to cache given that no file exceed minimum cache size. We achieved a unique placement of a file within a cluster of helpers to increase the number of files cached within a cluster. Further, our experimental evaluation demonstrates that our algorithm increases local and neighbor hit ratios as compared to a random placement, which in turn significantly decreases the traffic that goes over the backhaul bottleneck link.

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