SGIDN-LCD: An Appearance-based Loop Closure Detection Algorithm using Superpixel Grids and Incremental Dynamic Nodes

Loop Closure Detection (LCD) is an essential component of visual simultaneous localization and mapping (SLAM) systems. It enables the recognition of previously visited scenes to eliminate pose and map estimate drifts arising from long-term exploration. However, current appearance-based LCD methods face significant challenges, including high computational costs, viewpoint variance, and dynamic objects in scenes. This paper introduces an online based on Superpixel Grids (SGs) LCD approach, SGIDN-LCD, to find similarities between scenes via hand-crafted features extracted from SGs. Unlike traditional Bag-of-Words (BoW) models requiring pre-training, we propose an adaptive mechanism to group similar images called $\textbf{\textit{dynamic}}$ $\textbf{\textit{node}}$, which incremental adjusts the database in an online manner, allowing for efficient retrieval of previously viewed images. Experimental results demonstrate the SGIDN-LCD significantly improving LCD precision-recall and efficiency. Moreover, our proposed overall LCD method outperforms state-of-the-art approaches on multiple typical datasets

PLD-SLAM: A Real-Time Visual SLAM Using Points and Line Segments in Dynamic Scenes

In this paper, we consider the problems in the practical application of visual simultaneous localization and mapping (SLAM). With the popularization and application of the technology in wide scope, the practicability of SLAM system has become a new hot topic after the accuracy and robustness, e.g., how to keep the stability of the system and achieve accurate pose estimation in the low-texture and dynamic environment, and how to improve the universality and real-time performance of the system in the real scenes, etc. This paper proposes a real-time stereo indirect visual SLAM system, PLD-SLAM, which combines point and line features, and avoid the impact of dynamic objects in highly dynamic environments. We also present a novel global gray similarity (GGS) algorithm to achieve reasonable keyframe selection and efficient loop closure detection (LCD). Benefiting from the GGS, PLD-SLAM can realize real-time accurate pose estimation in most real scenes without pre-training and loading a huge feature dictionary model. To verify the performance of the proposed system, we compare it with existing state-of-the-art (SOTA) methods on the public datasets KITTI, EuRoC MAV, and the indoor stereo datasets provided by us, etc. The experiments show that the PLD-SLAM has better real-time performance while ensuring stability and accuracy in most scenarios. In addition, through the analysis of the experimental results of the GGS, we can find it has excellent performance in the keyframe selection and LCD

ETCH: Efficient Channel Hopping for Communication Rendezvous in Dynamic Spectrum Access Networks

In a dynamic spectrum access (DSA) network, communication rendezvous is the first step for two secondary users to be able to communicate with each other. In this step, the pair of secondary users meet on the same channel, over which they negotiate on the communication parameters, to establish the communication link. This paper presents ETCH, Efficient Channel Hopping based MAC-layer protocols for communication rendezvous in DSA networks. We propose two protocols, SYNC-ETCH and ASYNC-ETCH. Both protocols achieve better time-to-rendezvous and throughput compared to previous work

Deep Dictionary Learning with An Intra-class Constraint

In recent years, deep dictionary learning (DDL)has attracted a great amount of attention due to its effectiveness for representation learning and visual recognition.~However, most existing methods focus on unsupervised deep dictionary learning, failing to further explore the category information.~To make full use of the category information of different samples, we propose a novel deep dictionary learning model with an intra-class constraint (DDLIC) for visual classification. Specifically, we design the intra-class compactness constraint on the intermediate representation at different levels to encourage the intra-class representations to be closer to each other, and eventually the learned representation becomes more discriminative.~Unlike the traditional DDL methods, during the classification stage, our DDLIC performs a layer-wise greedy optimization in a similar way to the training stage. Experimental results on four image datasets show that our method is superior to the state-of-the-art methods.Comment: 6 pages, 3 figures, 2 tables. It has been accepted in ICME202

Simulation of Particle Mixing and Separation in Multi-Component Fluidized Bed Using Eulerian-Eulerian Method: A Review

In practical engineering applications, the mixing and separation behavior of multi-component particles is importance to the fluidized bed operation. The development of many practical processes is inseparable from the knowledge of particle mixing and separation, such as material processing of ash-soluble coal gasification, multi-phase flow in boilers, and petrochemical catalytic processes. In recent years, due to the obvious advantages of the Eulerian–Eulerian model, many researchers at home and abroad have used it to study the mixing and separation behavior of particles. The paper reviews the use of Eulerian–Eulerian model to study the mixing and separation of multi-component particles in fluidized beds. The Eulerian–Eulerian model describes the gas-phase and each of the individual particles as continuums. The mechanism of particle mixing and separation, the influence of different factors on the particle mixing and separation including differences in particle size and density, the differences in apparent air velocity, the differences in model factors are discussed. Finally, an outlook for the use of Eulerian–Eulerian model to study the mixing and separation behavior of three component particles and related research on the drag model between particles

Evaluation of mixing and mixing rate in a multiple spouted bed by image processing technique

Mixing efficiency is one of the most significant factors, affecting both performance and scale-up of a gas-solid reactor system. This paper presents an experimental investigation on the particle mixing in a multiple spouted bed. Image processing technique was used to extract the real-time information concerning the distribution of particle components (bed materials and tracer particles). A more accurate definition of the tracer concentration was developed to calculate the mixing index. According to the visual observation and image analysis, the mixing mechanism was revealed and the mixing rate was evaluated. Based on these results, the effects of operation parameters on the mixing rate were discussed in terms of the flow patterns. It is found that the detection of the pixel distribution of each component in RGB images is not affected by the interference of air void, thus maintaining good measurement accuracy. Convective transportation controls the particle mixing in the internal jet and spout, while shear dominants the particle mixing in the dense moving region. Global mixing takes place only when the path from one spout cell to the other is open. This path can be formed either by the bubbles or particle circulation flows. The mixing rate is linked to the bubble motion and particle circulation. Provided that there are interactions between the spout cells, any parameters promoting the bubble motion and circulation can increase the mixing rate. Finally, a mixing pattern diagram was constructed to establish the connection between the flow structure and mixing intensity

Construction of a complete set of orthogonal Fourier-Mellin moment invariants for pattern recognition applications

International audienceThe completeness property of a set of invariant descriptors is of fundamental importance from the theoretical as well as the practical points of view. In this paper, we propose a general approach to construct a complete set of orthogonal Fourier-Mellin moment (OFMM) invariants. By establishing a relationship between the OFMMs of the original image and those of the image having the same shape but distinct orientation and scale, a complete set of scale and rotation invariants is derived. The efficiency and the robustness to noise of the method for recognition tasks are shown by comparing it with some existing methods on several data sets

Multiplexed Frequency-Selective Incoherent Holography

We propose a new incoherent optical holographic spectrum stripping reconstruction method, called incoherent multiplexing frequency-selective holography, which compresses two or more on-axis holograms into a single multiplexed on-axis hologram without loss of magnification and resolution. The technique described in this chapter effectively suppresses the background bias term and conjugate term. The acquired spectrum is obtained by stripping in the overlapping confounding correlation terms. The experimental results show the potential of the method in areas such as compressed holography and extended field of view imaging

Designer Amphiphilic Short Peptides Enhance Thermal Stability of Isolated Photosystem-I

Stability of membrane protein is crucial during protein purification and crystallization as well as in the fabrication of protein-based devices. Several recent studies have examined how various surfactants can stabilize membrane proteins out of their native membrane environment. However, there is still no single surfactant that can be universally employed for all membrane proteins. Because of the lack of knowledge on the interaction between surfactants and membrane proteins, the choice of a surfactant for a specific membrane protein remains purely empirical. Here we report that a group of short amphiphilic peptides improve the thermal stability of the multi-domain protein complex photosystem-I (PS-I) in aqueous solution and that the peptide surfactants have obvious advantages over other commonly used alkyl chain based surfactants. Of all the short peptides studied, Ac-I5K2-CONH2 (I5K2) showed the best stabilizing effect by enhancing the melting temperature of PS-I from 48.0°C to 53.0°C at concentration of 0.65 mM and extending the half life of isolated PS-I significantly. AFM experiments showed that PS-I/I5K2/Triton X-100 formed large and stable vesicles and thus provide interfacial environment mimicking that of native membranes, which may partly explain why I5K2 enhanced the thermal stability of PS-I. Hydrophobic and hydrophilic group length of IxKy had an important influence on the stabilization of PS-I. Our results showed that longer hydrophobic group was more effective in stabilizing PS-I. These simple short peptides therefore exhibit significant potential for applications in membrane protein studies