Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

3D reconstruction of bird flight trajectories using a single video camera.

ABSTRACT: Video cameras are finding increasing use in the study and analysis of bird flight over short ranges. However, reconstruction of flight trajectories in three dimensions typically requires the use of multiple cameras and elaborate calibration procedures. We present an alternative approach that uses a single video camera and a simple calibration procedure for the reconstruction of such trajectories. The technique combines prior knowledge of the wingspan of the bird with a camera calibration procedure that needs to be used only once in the lifetime of the system. The system delivers the exact 3D coordinates of the position of the bird at the time of every full wing extension and uses interpolated height estimates to compute the 3D positions of the bird in the video frames between successive wing extensions. The system is inexpensive, compact and portable, and can be easily deployed in the laboratory as well as the field.

SUBMITTER: Srinivasan MV

PROVIDER: S-EPMC9401184 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Publications

3D reconstruction of bird flight trajectories using a single video camera.

Srinivasan M V MV Vo H D HD Schiffner I I

PloS one 20220824 8

Video cameras are finding increasing use in the study and analysis of bird flight over short ranges. However, reconstruction of flight trajectories in three dimensions typically requires the use of multiple cameras and elaborate calibration procedures. We present an alternative approach that uses a single video camera and a simple calibration procedure for the reconstruction of such trajectories. The technique combines prior knowledge of the wingspan of the bird with a camera calibration procedu ...[more]

PMID: 36001605

Similar Datasets

Video-rate nanoscopy using sCMOS camera-specific single-molecule localization algorithms.

Project description:Newly developed scientific complementary metal-oxide semiconductor (sCMOS) cameras have the potential to dramatically accelerate data acquisition, enlarge the field of view and increase the effective quantum efficiency in single-molecule switching nanoscopy. However, sCMOS-intrinsic pixel-dependent readout noise substantially lowers the localization precision and introduces localization artifacts. We present algorithms that overcome these limitations and that provide unbiased, precise localization of single molecules at the theoretical limit. Using these in combination with a multi-emitter fitting algorithm, we demonstrate single-molecule localization super-resolution imaging at rates of up to 32 reconstructed images per second in fixed and living cells.

| S-EPMC3696415 | biostudies-literature

3D reconstruction of small bowel lesions using stereo camera-based capsule endoscopy.

Project description:Three-dimensional (3D) reconstruction of capsule endoscopic images has been attempted for a long time to obtain more information on small bowel structures. Due to the limited hardware resources of capsule size and battery capacity, software approaches have been studied but have mainly exhibited inherent limitations. Recently, stereo camera-based capsule endoscopy, which can perform hardware-enabled 3D reconstruction, has been developed. We aimed to evaluate the feasibility of newly developed 3D capsule endoscopy in clinical practice. This study was a prospective, single-arm, feasibility study conducted at two university-affiliated hospitals in South Korea. Small bowel evaluation was performed using a newly developed 3D capsule endoscope for patients with obscure gastrointestinal bleeding, suspected or established Crohn's disease, small bowel tumors, and abdominal pain of unknown origin. We assessed the technical limitations, performance, and safety of the new capsule endoscope. Thirty-one patients (20 men and 11 women; mean age: 44.5 years) were enrolled. There was no technical defect preventing adequate visualization of the small bowel. The overall completion rate was 77.4%, the detection rate was 64.5%, and there was no capsule retention. All capsule endoscopic procedures were completed uneventfully. In conclusion, newly developed 3D capsule endoscopy was safe and feasible, showing similar performance as conventional capsule endoscopy. Newly added features of 3D reconstruction and size measurement are expected to be useful in the characterization of subepithelial tumours.

| S-EPMC7138835 | biostudies-literature

Reconstruction of complex single-cell trajectories using CellRouter.

Project description:A better understanding of the cell-fate transitions that occur in complex cellular ecosystems in normal development and disease could inform cell engineering efforts and lead to improved therapies. However, a major challenge is to simultaneously identify new cell states, and their transitions, to elucidate the gene expression dynamics governing cell-type diversification. Here, we present CellRouter, a multifaceted single-cell analysis platform that identifies complex cell-state transition trajectories by using flow networks to explore the subpopulation structure of multi-dimensional, single-cell omics data. We demonstrate its versatility by applying CellRouter to single-cell RNA sequencing data sets to reconstruct cell-state transition trajectories during hematopoietic stem and progenitor cell (HSPC) differentiation to the erythroid, myeloid and lymphoid lineages, as well as during re-specification of cell identity by cellular reprogramming of monocytes and B-cells to HSPCs. CellRouter opens previously undescribed paths for in-depth characterization of complex cellular ecosystems and establishment of enhanced cell engineering approaches.

| S-EPMC5832860 | biostudies-literature

3D Bird Reconstruction: a Dataset, Model, and Shape Recovery from a Single View.

Project description:Automated capture of animal pose is transforming how we study neuroscience and social behavior. Movements carry important social cues, but current methods are not able to robustly estimate pose and shape of animals, particularly for social animals such as birds, which are often occluded by each other and objects in the environment. To address this problem, we first introduce a model and multi-view optimization approach, which we use to capture the unique shape and pose space displayed by live birds. We then introduce a pipeline and experiments for keypoint, mask, pose, and shape regression that recovers accurate avian postures from single views. Finally, we provide extensive multi-view keypoint and mask annotations collected from a group of 15 social birds housed together in an outdoor aviary. The project website with videos, results, code, mesh model, and the Penn Aviary Dataset can be found at https://marcbadger.github.io/avian-mesh.

| S-EPMC9273110 | biostudies-literature

Real-Time Dynamic 3D Shape Reconstruction with SWIR InGaAs Camera.

Project description:In this paper, a real-time, dynamic three-dimensional (3D) shape reconstruction scheme based on the Fourier-transform profilometry (FTP) method is achieved with a short-wave infrared (SWIR) indium gallium arsenide (InGaAs) camera for monitoring applications in low illumination environments. A SWIR 3D shape reconstruction system is built for generating and acquiring the SWIR two-dimensional (2D) fringe pattern of the target. The depth information of the target is reconstructed by employing an improved FTP method, which has the advantages of high reconstruction accuracy and speed. The maximum error in depth for static 3D shape reconstruction is 1.15 mm for a plastic model with a maximum depth of 36 mm. Meanwhile, a real-time 3D shape reconstruction with a frame rate of 25 Hz can be realized by this system, which has great application prospects in real-time dynamic 3D shape reconstruction, such as low illumination monitoring. In addition, for real-time dynamic 3D shape reconstruction, without considering the edge areas, the maximum error in depth among all frames is 1.42 mm for a hemisphere with a depth of 35 mm, and the maximum error of the average of all frames in depth is 0.52 mm.

| S-EPMC7014486 | biostudies-literature

Rapid 3D Reconstruction for Image Sequence Acquired from UAV Camera.

Project description:In order to reconstruct three-dimensional (3D) structures from an image sequence captured by unmanned aerial vehicles' camera (UAVs) and improve the processing speed, we propose a rapid 3D reconstruction method that is based on an image queue, considering the continuity and relevance of UAV camera images. The proposed approach first compresses the feature points of each image into three principal component points by using the principal component analysis method. In order to select the key images suitable for 3D reconstruction, the principal component points are used to estimate the interrelationships between images. Second, these key images are inserted into a fixed-length image queue. The positions and orientations of the images are calculated, and the 3D coordinates of the feature points are estimated using weighted bundle adjustment. With this structural information, the depth maps of these images can be calculated. Next, we update the image queue by deleting some of the old images and inserting some new images into the queue, and a structural calculation of all the images can be performed by repeating the previous steps. Finally, a dense 3D point cloud can be obtained using the depth-map fusion method. The experimental results indicate that when the texture of the images is complex and the number of images exceeds 100, the proposed method can improve the calculation speed by more than a factor of four with almost no loss of precision. Furthermore, as the number of images increases, the improvement in the calculation speed will become more noticeable.

| S-EPMC5795716 | biostudies-other

A fast 3D reconstruction system with a low-cost camera accessory.

Project description:Photometric stereo is a three dimensional (3D) imaging technique that uses multiple 2D images, obtained from a fixed camera perspective, with different illumination directions. Compared to other 3D imaging methods such as geometry modeling and 3D-scanning, it comes with a number of advantages, such as having a simple and efficient reconstruction routine. In this work, we describe a low-cost accessory to a commercial digital single-lens reflex (DSLR) camera system allowing fast reconstruction of 3D objects using photometric stereo. The accessory consists of four white LED lights fixed to the lens of a commercial DSLR camera and a USB programmable controller board to sequentially control the illumination. 3D images are derived for different objects with varying geometric complexity and results are presented, showing a typical height error of <3 mm for a 50 mm sized object.

| S-EPMC4460880 | biostudies-literature

Time-of-Flight Microwave Camera.

Project description:Microwaves can penetrate many obstructions that are opaque at visible wavelengths, however microwave imaging is challenging due to resolution limits associated with relatively small apertures and unrecoverable "stealth" regions due to the specularity of most objects at microwave frequencies. We demonstrate a multispectral time-of-flight microwave imaging system which overcomes these challenges with a large passive aperture to improve lateral resolution, multiple illumination points with a data fusion method to reduce stealth regions, and a frequency modulated continuous wave (FMCW) receiver to achieve depth resolution. The camera captures images with a resolution of 1.5 degrees, multispectral images across the X frequency band (8 GHz-12 GHz), and a time resolution of 200 ps (6 cm optical path in free space). Images are taken of objects in free space as well as behind drywall and plywood. This architecture allows "camera-like" behavior from a microwave imaging system and is practical for imaging everyday objects in the microwave spectrum.

| S-EPMC4592950 | biostudies-literature

Video reconstruction from a single motion blurred image using learned dynamic phase coding.

Project description:Video reconstruction from a single motion-blurred image is a challenging problem, which can enhance the capabilities of existing cameras. Recently, several works addressed this task using conventional imaging and deep learning. Yet, such purely digital methods are inherently limited, due to direction ambiguity and noise sensitivity. Some works attempt to address these limitations with non-conventional image sensors, however, such sensors are extremely rare and expensive. To circumvent these limitations by simpler means, we propose a hybrid optical-digital method for video reconstruction that requires only simple modifications to existing optical systems. We use learned dynamic phase-coding in the lens aperture during image acquisition to encode motion trajectories, which serve as prior information for the video reconstruction process. The proposed computational camera generates a sharp frame burst of the scene at various frame rates from a single coded motion-blurred image, using an image-to-video convolutional neural network. We present advantages and improved performance compared to existing methods, with both simulations and a real-world camera prototype. We extend our optical coding to video frame interpolation and present robust and improved results for noisy videos.

| S-EPMC10442388 | biostudies-literature

Breathing Analysis Using Thermal and Depth Imaging Camera Video Records.

Project description:The paper is devoted to the study of facial region temperature changes using a simple thermal imaging camera and to the comparison of their time evolution with the pectoral area motion recorded by the MS Kinect depth sensor. The goal of this research is to propose the use of video records as alternative diagnostics of breathing disorders allowing their analysis in the home environment as well. The methods proposed include (i) specific image processing algorithms for detecting facial parts with periodic temperature changes; (ii) computational intelligence tools for analysing the associated videosequences; and (iii) digital filters and spectral estimation tools for processing the depth matrices. Machine learning applied to thermal imaging camera calibration allowed the recognition of its digital information with an accuracy close to 100% for the classification of individual temperature values. The proposed detection of breathing features was used for monitoring of physical activities by the home exercise bike. The results include a decrease of breathing temperature and its frequency after a load, with mean values -0.16 °C/min and -0.72 bpm respectively, for the given set of experiments. The proposed methods verify that thermal and depth cameras can be used as additional tools for multimodal detection of breathing patterns.

| S-EPMC5491982 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data