Shape Completion with Points in the Shadow

Single-view point cloud completion aims to recover the full geometry of an object based on only limited observation, which is extremely hard due to the data sparsity and occlusion. The core challenge is to generate plausible geometries to fill the unobserved part of the object based on a partial scan, which is under-constrained and suffers from a huge solution space. Inspired by the classic shadow volume technique in computer graphics, we propose a new method to reduce the solution space effectively. Our method considers the camera a light source that casts rays toward the object. Such light rays build a reasonably constrained but sufficiently expressive basis for completion. The completion process is then formulated as a point displacement optimization problem. Points are initialized at the partial scan and then moved to their goal locations with two types of movements for each point: directional movements along the light rays and constrained local movement for shape refinement. We design neural networks to predict the ideal point movements to get the completion results. We demonstrate that our method is accurate, robust, and generalizable through exhaustive evaluation and comparison. Moreover, it outperforms state-of-the-art methods qualitatively and quantitatively on MVP datasets.Comment: SIGGRAPH Aisa 2022 Conference Pape

The Dynamic Model Embed in Augmented Graph Cuts for Robust Hand Tracking and Segmentation in Videos

Segmenting human hand is important in computer vision applications, for example, sign language interpretation, human computer interaction, and gesture recognition. However, some serious bottlenecks still exist in hand localization systems such as fast hand motion capture, hand over face, and hand occlusions on which we focus in this paper. We present a novel method for hand tracking and segmentation based on augmented graph cuts and dynamic model. First, an effective dynamic model for state estimation is generated, which correctly predicts the location of hands probably having fast motion or shape deformations. Second, new energy terms are brought into the energy function to develop augmented graph cuts based on some cues, namely, spatial information, hand motion, and chamfer distance. The proposed method successfully achieves hand segmentation even though the hand passes over other skin-colored objects. Some challenging videos are provided in the case of hand over face, hand occlusions, dynamic background, and fast motion. Experimental results demonstrate that the proposed method is much more accurate than other graph cuts-based methods for hand tracking and segmentation

Relationship Templates for Synthesising Scene Variations

We propose a novel example-based approach to synthesize scenes with complex relations, e.g., when one object is 'hooked', 'surrounded', 'contained' or 'tucked into' another object. Existing relationship descriptors used in automatic scene synthesis methods are based on contacts or relative vectors connecting the object centers. Such descriptors do not fully capture the geometry of spatial interactions, and therefore cannot describe complex relationships. Our idea is to enrich the description of spatial relations between object surfaces by encoding the geometry of the open space around objects, and use this as a template for fitting novel objects. To this end, we introduce relationship templates as descriptors of complex relationships; they are computed from an example scene and combine the interaction bisector surface (IBS) with a novel feature called the space coverage feature (SCF), which encodes the open space in the frequency domain. New variations of a scene can be synthesized efficiently by fitting novel objects to the template. Our method greatly enhances existing automatic scene synthesis approaches by allowing them to handle complex relationships, as validated by our user studies. The proposed method generalizes well, as it can form complex relationships with objects that have a topology and geometry very different from the example scene

The Flow Field Analysis and Flow Calculation of Ultrasonic Flowmeter Based on the Fluent Software

We can build the three-dimensional structure model based on the Gambit software and achieve the distribution of flow field in the pipe and reflux flow condition at the position of transducer in regard to the real position of transducer according to the Fluent software. Under the framework, define the reflux length based on the distance of reflux along the channel and evaluate the effect of reflux on flow field. Then we can correct the power factor with the transmission speed difference method in the ideal condition and obtain the matching expression of power correction factor according to the practice model. In the end, analyze the simulation experience and produce the sample table based on the proposed model. The comparative analysis of test results and simulation results demonstrates the validity and feasibility of the proposed simulation method. The research in this paper will lay a foundation for further study on the optimization of ultrasonic flowmeter, enhance the measurement precision, and extend the application of engineering

Tree-Based Backtracking Orthogonal Matching Pursuit for Sparse Signal Reconstruction

Compressed sensing (CS) is a theory which exploits the sparsity characteristic of the original signal in signal sampling and coding. By solving an optimization problem, the original sparse signal can be reconstructed accurately. In this paper, a new Tree-based Backtracking Orthogonal Matching Pursuit (TBOMP) algorithm is presented with the idea of the tree model in wavelet domain. The algorithm can convert the wavelet tree structure to the corresponding relations of candidate atoms without any prior information of signal sparsity. Thus, the atom selection process will be more structural and the search space can be narrowed. Moreover, according to the backtracking process, the previous chosen atoms’ reliability can be detected and the unreliable atoms can be deleted at each iteration, which leads to an accurate reconstruction of the signal ultimately. Compared with other compressed sensing algorithms, simulation results show the proposed algorithm’s superior performance to that of several other OMP-type algorithms

Adverse drug events associated with linezolid administration: a real-world pharmacovigilance study from 2004 to 2023 using the FAERS database

Introduction: Linezolid is an oxazolidinone antibiotic that is active against drug-resistant Gram-positive bacteria and multidrug-resistant Mycobacterium tuberculosis. Real-world studies on the safety of linezolid in large populations are lacking. This study aimed to determine the adverse events associated with linezolid in real-world settings by analyzing data from the US Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS).Methods: We retrospectively extracted reports on adverse drug events (ADEs) from the FAERS database from the first quarter of 2004 to that of 2023. By using disproportionality analysis including reporting odds ratio (ROR), proportional reporting ratio (PRR), Bayesian Confidence Propagation Neural Network (BCPNN), along with the multi-item gamma Poisson shrinker (MGPS), we evaluated whether there was a significant association between linezolid and ADE. The time to onset of ADE was further analyzed in the general population and within each age, weight, reporting population, and weight subgroups.Results: A total of 11,176 reports of linezolid as the “primary suspected” drug and 263 significant adverse events of linezolid were identified, including some common adverse events such as thrombocytopenia (n = 1,139, ROR 21.98), anaemia (n = 704, ROR 7.39), and unexpected signals that were not listed on the drug label such as rhabdomyolysis (n = 90, ROR 4.33), and electrocardiogram QT prolonged (n = 73, ROR 4.07). Linezolid-induced adverse reactions involved 27 System Organ Class (SOC). Gender differences existed in ADE signals related to linezolid. The median onset time of all ADEs was 6 days, and most ADEs (n = 3,778) occurred within the first month of linezolid use but some may continue to occur even after a year of treatment (n = 46).Conclusion: This study reports the time to onset of adverse effects in detail at the levels of SOC and specific preferred term (PT). The results of our study provide valuable insights for optimizing the use of linezolid and reducing potential side effects, expected to facilitate the safe use of linezolid in clinical settings

Fuzzy logic controller based Genetic algorithm for semi-active suspension

521-527This study proposed a novel control scheme for multi-body semi-active suspension system (SASS), composed of a multibody model of SASS and a fuzzy logic controller based genetic algorithm (FLC-GA). ADAMS software was utilized to complete multi-body model of a full car SASS. Simulations with random road profile at two different speeds (25 m/s & 35 m/s) demonstrated that developed FLC-GA enhances performance of full car suspension system significantly and was more effective than passive suspension response