Image stitching with perspective-preserving warping

Image stitching algorithms often adopt the global transformation, such as homography, and work well for planar scenes or parallax free camera motions. However, these conditions are easily violated in practice. With casual camera motions, variable taken views, large depth change, or complex structures, it is a challenging task for stitching these images. The global transformation model often provides dreadful stitching results, such as misalignments or projective distortions, especially perspective distortion. To this end, we suggest a perspective-preserving warping for image stitching, which spatially combines local projective transformations and similarity transformation. By weighted combination scheme, our approach gradually extrapolates the local projective transformations of the overlapping regions into the non-overlapping regions, and thus the final warping can smoothly change from projective to similarity. The proposed method can provide satisfactory alignment accuracy as well as reduce the projective distortions and maintain the multi-perspective view. Experiments on a variety of challenging images confirm the efficiency of the approach.Comment: ISPRS 2016 - XXIII ISPRS Congress: Prague, Czech Republic, 201

The effect of BMP9 on inflammation in the early stage of pulpitis

Bone morphogenetic protein 9 (BMP9) tends to be associated with various inflammatory responses of diseases, but its relationship with pulpitis remains unknown. Objective: This study aimed to evaluate the effects and mechanisms of BMP9 in pulpitis. Methodology: A rat model of pulpitis was used to evaluate the expression of BMP9, which was also analysed in Porphyromonas gingivalis lipopolysaccharide (Pg-LPS)-stimulated human dental pulp cells (hDPCs). The effects and mechanism of BMP9 on the regulation of inflammatory factors and matrix metalloproteinase-2 (MMP2) were evaluated using real-time quantitative PCR, western blotting, and immunocytofluorescence. Moreover, the migration ability of THP-1 monocyte-macrophages, treated with inflammatory supernate inhibited by BMP9, was previously tested by a transwell migration assay. Finally, a direct rat pulp capping model was used to evaluate in vivo the influence of the overexpression of BMP9 in pulpitis. Results: The expression of BMP9 decreased after 24 h and increased after 3 and 7 d in rat pulpitis and inflammatory hDPCs. The overexpression of BMP9 inhibited the gene expression of inflammatory factors (IL-6, IL-8, and CCL2) and the secretion of IL-6 and MMP2 in Pg-LPS-stimulated hDPCs. The level of phosphorylated Smad1/5 was upregulated and the levels of phosphorylated ERK and JNK were downregulated. The inflammatory supernate of hDPCs inhibited by BMP9 reduced the migration of THP-1 cells. In rat pulp capping models, overexpressed BMP9 could partially restrain the development of dental pulp inflammation. Conclusion: This is the first study to confirm that BMP9 is involved in the occurrence and development of pulpitis and can partially inhibit its severity in the early stage. These findings provided a theoretical reference for future studies on the mechanism of pulpitis and application of bioactive molecules in vital pulp therapy

Slide-Transformer: Hierarchical Vision Transformer with Local Self-Attention

Self-attention mechanism has been a key factor in the recent progress of Vision Transformer (ViT), which enables adaptive feature extraction from global contexts. However, existing self-attention methods either adopt sparse global attention or window attention to reduce the computation complexity, which may compromise the local feature learning or subject to some handcrafted designs. In contrast, local attention, which restricts the receptive field of each query to its own neighboring pixels, enjoys the benefits of both convolution and self-attention, namely local inductive bias and dynamic feature selection. Nevertheless, current local attention modules either use inefficient Im2Col function or rely on specific CUDA kernels that are hard to generalize to devices without CUDA support. In this paper, we propose a novel local attention module, Slide Attention, which leverages common convolution operations to achieve high efficiency, flexibility and generalizability. Specifically, we first re-interpret the column-based Im2Col function from a new row-based perspective and use Depthwise Convolution as an efficient substitution. On this basis, we propose a deformed shifting module based on the re-parameterization technique, which further relaxes the fixed key/value positions to deformed features in the local region. In this way, our module realizes the local attention paradigm in both efficient and flexible manner. Extensive experiments show that our slide attention module is applicable to a variety of advanced Vision Transformer models and compatible with various hardware devices, and achieves consistently improved performances on comprehensive benchmarks. Code is available at https://github.com/LeapLabTHU/Slide-Transformer.Comment: Accepted to CVPR202

New Signal and Algorithms for 5G/6G High Precision Train Positioning in Tunnel with Leaky Coaxial Cable

High precision train positioning is a crucial component of intelligent transportation systems. Tunnels are commonly encountered in subways and mountainous regions. As part of the communication system infrastructure, Leaky CoaXial (LCX) Cable is widely equipped as antenna in tunnels with many advantages. LCX positioning holds great promise as a technology for rail applications in the upcoming B5G (beyond-5G) and 6G eras. This paper focuses on the LCX positioning methodology and proposes two novel algorithms along with a novel communication-positioning integration signal. Firstly, a novel algorithm called Multiple Slot Distinction (MSD) LCX positioning algorithm is proposed. The algorithm utilizes a generated pseudo spectrum to fully utilize the coupled signals radiated from different slots of LCX. This approach offers higher time resolution compared to traditional methods. To further improve the positioning accuracy to centimeter-level and increase the measuring frequency for fast trains, a novel communication-positioning integration signal is designed. It consists of traditional Positioning Reference Signal (PRS) and a significantly low power Fine Ranging Signal (FRS). FRS is configured to be continuous and superposed onto the cellular signal using Non-Orthogonal Multiple Access (NOMA) principle to minimize its interference to communication. A two-stage LCX positioning method is then executed: At the first stage, the closest slot between the receiver and LCX is estimated by the proposed MSD algorithm using PRS; At the second stage, centimeter-level positioning is achieved by tracking the carrier phase of the continuous FRS. This process is assisted by the closest slot estimation, which helps mitigate interference between neighboring slots and eliminate the integer ambiguities. Simulation results show our proposed LCX position methodology outperforms the existing ones and offer great potentials for future implementations

Soil texture and microorganisms dominantly determine the subsoil carbonate content in the permafrost-affected area of the Tibetan Plateau

Under climate warming conditions, storage and conversion of soil inorganic carbon (SIC) play an important role in regulating soil carbon (C) dynamics and atmospheric CO2 content in arid and semi-arid areas. Carbonate formation in alkaline soil can fix a large amount of C in the form of inorganic C, resulting in soil C sink and potentially slowing global warming trends. Therefore, understanding the driving factors affecting carbonate mineral formation can help better predict future climate change. Till date, most studies have focused on abiotic drivers (climate and soil), whereas a few examined the effects of biotic drivers on carbonate formation and SIC stock. In this study, SIC, calcite content, and soil microbial communities were analyzed in three soil layers (0–5 cm, 20–30 cm, and 50–60 cm) on the Beiluhe Basin of Tibetan Plateau. Results revealed that in arid and semi-arid areas, SIC and soil calcite content did not exhibit significant differences among the three soil layers; however, the main factors affecting the calcite content in different soil layers are different. In the topsoil (0–5 cm), the most important predictor of calcite content was soil water content. In the subsoil layers 20–30 cm and 50–60 cm, the ratio of bacterial biomass to fungal biomass (B/F) and soil silt content, respectively, had larger contributions to the variation of calcite content than the other factors. Plagioclase provided a site for microbial colonization, whereas Ca2+ contributed in bacteria-mediated calcite formation. This study aims to highlight the importance of soil microorganisms in managing soil calcite content and reveals preliminary results on bacteria-mediated conversion of organic to inorganic C

Assessment of small strain modulus in soil using advanced computational models

Abstract Small-strain shear modulus ( $$G_0$$ G 0 ) of soils is a crucial dynamic parameter that significantly impacts seismic site response analysis and foundation design. $$G_0$$ G 0 is susceptible to multiple factors, including soil uniformity coefficient ( $$C_u$$ C u ), void ratio (e), mean particle size ( $$d_{50}$$ d 50 ), and confining stress ( $$\sigma '$$ σ ′ ). This study aims to establish a $$G_0$$ G 0 database and suggests three advanced computational models for $$G_0$$ G 0 prediction. Nine performance indicators, including four new indices, are employed to calculate and analyze the model’s performance. The XGBoost model outperforms the other two models, with all three models achieving $$R^2$$ R 2 values exceeding 0.9, RMSE values below 30, MAE values below 25, VAF values surpassing 80%, and ARE values below 50%. Compared to the empirical formula-based traditional prediction models, the model proposed in this study exhibits better performance in IOS, IOA, a20-index, and PI metrics values. The model has higher prediction accuracy and better generalization ability

A Compensation Method for Airborne SAR with Varying Accelerated Motion Error

Motion error is one of the most serious problems in airborne synthetic aperture radar (SAR) data processing. For a smoothly distributing backscatter scene or a seriously speed-varying velocity platform, the autofocusing performances of conventional algorithms, e.g., map-drift (MD) or phase gradient autofocus (PGA) are limited by their estimators. In this paper, combining the trajectories measured by global position system (GPS) and inertial navigation system (INS), we propose a novel error compensation method for varying accelerated airborne SAR based on the best linear unbiased estimation (BLUE). The proposed compensating method is particularly intended for varying acceleration SAR or homogeneous backscatter scenes, the processing procedures and computational cost of which are much simpler and lower than those of MD and PGA algorithms

Data_Sheet_1_Soil texture and microorganisms dominantly determine the subsoil carbonate content in the permafrost-affected area of the Tibetan Plateau.PDF

Under climate warming conditions, storage and conversion of soil inorganic carbon (SIC) play an important role in regulating soil carbon (C) dynamics and atmospheric CO2 content in arid and semi-arid areas. Carbonate formation in alkaline soil can fix a large amount of C in the form of inorganic C, resulting in soil C sink and potentially slowing global warming trends. Therefore, understanding the driving factors affecting carbonate mineral formation can help better predict future climate change. Till date, most studies have focused on abiotic drivers (climate and soil), whereas a few examined the effects of biotic drivers on carbonate formation and SIC stock. In this study, SIC, calcite content, and soil microbial communities were analyzed in three soil layers (0–5 cm, 20–30 cm, and 50–60 cm) on the Beiluhe Basin of Tibetan Plateau. Results revealed that in arid and semi-arid areas, SIC and soil calcite content did not exhibit significant differences among the three soil layers; however, the main factors affecting the calcite content in different soil layers are different. In the topsoil (0–5 cm), the most important predictor of calcite content was soil water content. In the subsoil layers 20–30 cm and 50–60 cm, the ratio of bacterial biomass to fungal biomass (B/F) and soil silt content, respectively, had larger contributions to the variation of calcite content than the other factors. Plagioclase provided a site for microbial colonization, whereas Ca2+ contributed in bacteria-mediated calcite formation. This study aims to highlight the importance of soil microorganisms in managing soil calcite content and reveals preliminary results on bacteria-mediated conversion of organic to inorganic C.</p