Dropped Objects Recognition in Offshore Operations Based on Computer Vision and Artificial Intelligence

We are more interested in recovering and salvaging containers which may be loaded with either valuable or harmful substances. Therefore, we designed various container models to account for different loading conditions and then exported them to a 3D printer. Six small container models were dropped into the trailer pool at the University of New Orleans (UNO) as planned at angles of 0°, 45°, and 90°. After collecting all the videos using a high-definition camera set outside the tank, we perform pre-processing tasks on the videos in preparation for model training. The two-phase angle classification method uses a pretrained ResNet50 model trained on ImageNet as a feature extractor to generate latent features to train a gated recurrent unit (GRU) model to classify the entry angle of dropped objects. Furthermore, the output of the recognition phase, including the shape of the dropped object and the initial drop angle, is used as input to another in-house tool, the Dropped Object Simulator (DROBS), which was developed in MATLAB using simulate the trajectory and determine the final landing position

A Study on the Explicit Expression of Critical Stress and Euler Stress and its Application

Both the tangent modulus theory and the double modulus theory are classical theories which can be applied to the elastic-plastic stability analysis of columns. In the traditional tangent modulus theory, numerous iterations are required to calculate the critical buckling stress and this makes the method very time-consuming. In this paper, an explicit formula for establishing a direct correlation between the critical stress and the Euler stress has been proposed to reduce trial calculations. This formula can be applied to spherical shells by simplifying their stiffened plates to the form of beams on elastic foundations. The explicit expressions of both modulus theories can be used to calculate the ultimate strength of a spherical shell under pressure. The results from the proposed expression are compared with experimental results and other numerical results

Co-interest Person Detection from Multiple Wearable Camera Videos

Wearable cameras, such as Google Glass and Go Pro, enable video data collection over larger areas and from different views. In this paper, we tackle a new problem of locating the co-interest person (CIP), i.e., the one who draws attention from most camera wearers, from temporally synchronized videos taken by multiple wearable cameras. Our basic idea is to exploit the motion patterns of people and use them to correlate the persons across different videos, instead of performing appearance-based matching as in traditional video co-segmentation/localization. This way, we can identify CIP even if a group of people with similar appearance are present in the view. More specifically, we detect a set of persons on each frame as the candidates of the CIP and then build a Conditional Random Field (CRF) model to select the one with consistent motion patterns in different videos and high spacial-temporal consistency in each video. We collect three sets of wearable-camera videos for testing the proposed algorithm. All the involved people have similar appearances in the collected videos and the experiments demonstrate the effectiveness of the proposed algorithm.Comment: ICCV 201

Time-domain Simulation of Multibody Floating Systems based on State-space Modeling Technology

A numerical scheme to simulate time-domain motion responses of multibody floating systems has been successfully proposed. This scheme is integrated into a time-domain simulation tool, with fully coupled hydrodynamic coefficients obtained from the hydrodynamic software - WAMIT which solves the Boundary Value Problem (BVP). The equations of motion are transformed into standard state-space format, using the constant coefficient approximation and the impulse response function method. Thus the Ordinary Differential Equation (ODE) solvers in MATLAB can be directly employed. The time-domain responses of a single spar at sea are initially obtained. The optimal Linear Quadratic Regulator (LQR) controller is further applied to this single spar, by assuming that the Dynamic Positioning (DP) system can provide the optimized thruster forces. Various factors that affect the controlling efficiency, e.g., the time steps ∆τ and ∆t, the weighting factors(Q,R), are further investigated in detail. Next, a two-body floating system is studied. The response amplitude operators (RAOs) of each body are calculated and compared with the single body case. Then the effects of the body-to-body interaction coefficients on the time-domain responses are further investigated. Moreover, the mean drift force is incorporated in the DP system to further mitigate the motion responses of each body. Finally, this tool is extended to a three-body floating system, with the relative motions between them derived