MC-NeRF: Muti-Camera Neural Radiance Fields for Muti-Camera Image Acquisition Systems

Neural Radiance Fields (NeRF) employ multi-view images for 3D scene representation and have shown remarkable performance. As one of the primary sources of multi-view images, multi-camera systems encounter challenges such as varying intrinsic parameters and frequent pose changes. Most previous NeRF-based methods often assume a global unique camera and seldom consider scenarios with multiple cameras. Besides, some pose-robust methods still remain susceptible to suboptimal solutions when poses are poor initialized. In this paper, we propose MC-NeRF, a method can jointly optimize both intrinsic and extrinsic parameters for bundle-adjusting Neural Radiance Fields. Firstly, we conduct a theoretical analysis to tackle the degenerate case and coupling issue that arise from the joint optimization between intrinsic and extrinsic parameters. Secondly, based on the proposed solutions, we introduce an efficient calibration image acquisition scheme for multi-camera systems, including the design of calibration object. Lastly, we present a global end-to-end network with training sequence that enables the regression of intrinsic and extrinsic parameters, along with the rendering network. Moreover, most existing datasets are designed for unique camera, we create a new dataset that includes four different styles of multi-camera acquisition systems, allowing readers to generate custom datasets. Experiments confirm the effectiveness of our method when each image corresponds to different camera parameters. Specifically, we adopt up to 110 images with 110 different intrinsic and extrinsic parameters, to achieve 3D scene representation without providing initial poses. The Code and supplementary materials are available at https://in2-viaun.github.io/MC-NeRF.Comment: This manuscript is currently under revie

PointGPT: Auto-regressively Generative Pre-training from Point Clouds

Large language models (LLMs) based on the generative pre-training transformer (GPT) have demonstrated remarkable effectiveness across a diverse range of downstream tasks. Inspired by the advancements of the GPT, we present PointGPT, a novel approach that extends the concept of GPT to point clouds, addressing the challenges associated with disorder properties, low information density, and task gaps. Specifically, a point cloud auto-regressive generation task is proposed to pre-train transformer models. Our method partitions the input point cloud into multiple point patches and arranges them in an ordered sequence based on their spatial proximity. Then, an extractor-generator based transformer decoder, with a dual masking strategy, learns latent representations conditioned on the preceding point patches, aiming to predict the next one in an auto-regressive manner. Our scalable approach allows for learning high-capacity models that generalize well, achieving state-of-the-art performance on various downstream tasks. In particular, our approach achieves classification accuracies of 94.9% on the ModelNet40 dataset and 93.4% on the ScanObjectNN dataset, outperforming all other transformer models. Furthermore, our method also attains new state-of-the-art accuracies on all four few-shot learning benchmarks.Comment: 9 pages, 2 figure

Effects of oxycodone hydrochloride and dezocine on hemodynamics and levels of inflammatory factors in patients receiving gynecological laparoscopic surgery under general anesthesia

We aimed to compare the effects of oxycodone hydrochloride and dezocine on hemodynamics and inflammatory factors in patients receiving gynecological laparoscopic surgery under general anesthesia. A total of 246 patients were divided into group A and B (n=123). Hemorheology indices were recorded 5 min after anesthesia (T0), 1 min after pneumoperitoneum (T1), when position was changed 5 min after pneumoperitoneum (T2), 15 min after pneumoperitoneum (T3), 1 min (T4) and 5 min (T5) after position was restored. Visual analogue scale scores 1, 2, 6, 12, 24 and 48 h after operation were recorded. Postoperative adverse reactions and visceral pain were observed. The expression levels of inflammatory factors were detected by enzyme-linked immunosorbent assay 12 h after operation. Compared with group A, group B had higher heart rate and mean arterial pressure at T2, lower central venous pressure and cardiac output at T1-T3, and higher systemic vascular resistance at T1-T5 (P<0.05). The incidence rate of pain syndrome in group A was lower (P<0.05). Group A had lower tumor necrosis factor-alpha and interleukin-6 expression levels and higher interleukin-10 level than those of group B (P<0.05). For gynecological laparoscopic surgery, oxycodone preemptive analgesia has superior outcomes to those of dezocine

The influence of acoustic field induced by HRT on oscillation behavior of a single droplet

This paper presents an experimental and theoretical study on the effects of an acoustic field induced by Hartmann Resonance Tube (HRT) on droplet deformation behavior. The characteristics of the acoustic field generated by HRT are investigated. Results show that the acoustic frequency decreases with the increase of the resonator length, the sound pressure level (SPL) increases with the increase of nozzle pressure ratio (NPR), and it is also noted that increasing resonator length can cause SPL to decrease, which has rarely been reported in published literature. Further theoretical analysis reveals that the resonance frequency of a droplet has several modes, and when the acoustic frequency equals the droplet's frequency, heightened droplet responses are observed with the maximum amplitude of the shape oscillation. The experimental results for different resonator cavity lengths, nozzle pressure ratios and droplet diameters confirm the non-linear nature of this problem, and this conclusion is in good agreement with theoretical analysis. Measurements by high speed camera have shown that the introduction of an acoustic field can greatly enhance droplet oscillation, which means with the use of an ultrasonic atomizer based on HRT, the quality of atomization and combustion can be highly improved

U-model-based two-degree-of-freedom internal model control of nonlinear dynamic systems

This paper proposes a U-Model-Based Two-Degree-of-Freedom Internal Model Control (UTDF-IMC) structure with strength in nonlinear dynamic inversion, and separation of tracking design and robustness design. This approach can effectively accommodate modeling error and disturbance while removing those widely used linearization techniques for nonlinear plants/processes. To assure the expansion and applications, it analyses the key properties associated with the UTDF-IMC. For initial benchmark testing, computational experiments are conducted using MATLAB/Simulink for two mismatched linear and nonlinear plants. Further tests consider an industrial system, in which the IMC of a Permanent Magnet Synchronous Motor (PMSM) is simulated to demonstrate the effectiveness of the design procedure for potential industrial applications

Case report: Resection of a giant right ventricular myxoma

Myxoma constitutes the main subtype of all benign cardiac tumors, tending to be more common in women and occurring mostly in the left and right atria. Its classic clinical presentations are intracardiac obstruction, embolization, and systemic or constitutional symptoms, such as fever, in decreasing order. Several imaging techniques such as echocardiography, computed tomography, and angiocardiography contribute to the diagnosis of myxoma, ruling out significant coronary diseases, and assessment of myocardial invasion and tumor involvement of adjacent structures. Surgical resection is the only effective therapeutic option for patients with cardiac myxoma. Here, we report a unique case of a middle-aged man who presented with a giant myxoma and a 3-day history of chest tightness and shortness of breath after physical activity. Subsequently, transthoracic echocardiography revealed a mass of solid echodensity located within the right ventricle, complicated by abnormal hemodynamics. A cardiac computed tomographic angiography showed a large homogeneous density filling defect consuming most parts of the right ventricle and protruding from beat to beat. A surgical resection and histological study later successfully confirmed the diagnosis, and the patient's postoperative recovery course was found to be uneventful