Search results for "Robustness"
showing 10 items of 512 documents
3D Reconstruction of Dynamic Vehicles using Sparse 3D-Laser-Scanner and 2D Image Fusion
2016
International audience; Map building becomes one of the most interesting research topic in computer vision field nowadays. To acquire accurate large 3D scene reconstructions, 3D laser scanners are recently developed and widely used. They produce accurate but sparse 3D point clouds of the environments. However, 3D reconstruction of rigidly moving objects along side with the large-scale 3D scene reconstruction is still lack of interest in many researches. To achieve a detailed object-level 3D reconstruction, a single scan of point cloud is insufficient due to their sparsity. For example, traditional Iterative Closest Point (ICP) registration technique or its variances are not accurate and rob…
A novel meta-heuristic optimization algorithm based MPPT control technique for PV systems under complex partial shading condition
2021
Abstract The need to combat the increase in global warming is well taken by solar energy lead renewable energy resources. The techno-economic feasibility of solar systems in the form of photovoltaic (PV) generation is highly dependent upon its operating conditions. The nonlinear control problem is further worsened by partial shading (PS) environment causing major power losses. Bio-inspired maximum power point tracking (MPPT) control techniques, in literature, exhibit some major common drawbacks such as high tracking and settling time, oscillations at global maxima (GM), and local maxima (LM) trapping under PS conditions. This paper presents a novel search and rescue (SRA) optimization algor…
Subsequent Keyframe Generation for Visual Servoing
2021
International audience; In this paper, we study the problem of autonomous and reliable positioning of a camera w.r.t. an object when only this latter is known but not the rest of the scene. We propose to combine the advantages and efficiency of a visual servoing scheme and the generalization ability of a generative adversarial network. The paper describes how to efficiently create a synthetic dataset in order to train a network that predicts an intermediate visual keyframe between two images. Subsequent predictions are used as visual features to autonomously converge towards the desired pose even for large displacements. We show that the proposed method can be used without any prior knowled…
On the Robustness of Deep Features for Audio Event Classification in Adverse Environments
2018
Deep features, responses to complex input patterns learned within deep neural networks, have recently shown great performance in image recognition tasks, motivating their use for audio analysis tasks as well. These features provide multiple levels of abstraction which permit to select a sufficiently generalized layer to identify classes not seen during training. The generalization capability of such features is very useful due to the lack of complete labeled audio datasets. However, as opposed to classical hand-crafted features such as Mel-frequency cepstral coefficients (MFCCs), the performance impact of having an acoustically adverse environment has not been evaluated in detail. In this p…
The stability problem and noisy projections in discrete tomography
2004
Abstract The new field of research of discrete tomography will be described in this paper. It differs from standard computerized tomography in the reduced number of projections. It needs ad hoc algorithms which usually are based on the definition of the model of the object to reconstruct. The main problems will be introduced and an experimental simulation will prove the robustness of a slightly modified version of a well known method for the reconstruction of binary planar convex sets, even in case of projections affected by error. To the best of our knowledge this is one of the first experimental study of the stability problem with a statistical approach. Prospective applications include c…
Avoiding Demand Amplification Phenomenon via Hi-tech Application: A What-If Supply Chain Analysis
2010
The well-known deleterious effect of the amplification of variance of order rates in multi-echelon systems, commonly known as demand amplification phenomenon or bullwhip effect, still presents new challenges and continues to fascinate the operations management community. Recently this research field is focusing on the study of robustness of bullwhip avoidance techniques under uncertainty, as environmental conditions often determine variations in processes, with regards to production and delivery lead time, and variations in the parameters of the decision policies. This work aims at quantifying the efficacy of bullwhip dampening techniques and at verifying this efficacy against variations in…
A vision-based fully automated approach to robust image cropping detection
2020
Abstract The definition of valid and robust methodologies for assessing the authenticity of digital information is nowadays critical to contrast social manipulation through the media. A key research topic in multimedia forensics is the development of methods for detecting tampered content in large image collections without any human intervention. This paper introduces AMARCORD (Automatic Manhattan-scene AsymmetRically CrOpped imageRy Detector), a fully automated detector for exposing evidences of asymmetrical image cropping on Manhattan-World scenes. The proposed solution estimates and exploits the camera principal point, i.e., a physical feature extracted directly from the image content th…
Robust Dynamic Comfort Modeling for Motorcycle Riding
2014
Comfort modeling is considered a prerequisite in motorcycle design, primarily to address safety concerns and to position the product on the market. However, a comprehensive methodology for comfort modeling during the earliest development phases of a motorcycle model is still missing. Anthropometrical variation is the main noise factor to consider in comfort modeling in relation to the unavoidable variability of body segments. However, comfort is a subjective concept influencing riders' choice of motorcycle model. This work is a generalization of the robust ergonomic design methodology aimed at designing products whose ergonomic performance is insensitive to anthropometrical variation. This …
Improving Reliability of Road Safety Estimates Based on High Correlated Accident Counts
2007
Calibrating a safety performance function (SPF) with many years of accident data creates a temporal correlation that traditional model calibration procedures cannot deal with. It is well known that generalized estimating equations (GEE) models are able to incorporate trends into accident data and thus overcome difficulties in accounting for correlation; the usual application of GEEs to safety analysis uses robust (or sandwich) estimates of regression coefficients under the independence hypothesis for the working correlation matrix. This practice is justified by the robustness of the GEE procedure against misspecification of the response correlation structure. Nevertheless, with this method…
DECENTRALIZED SUBSPACE PROJECTION IN LARGE NETWORKS
2018
A great number of applications in wireless sensor networks involve projecting a vector of observations onto a subspace dictated by prior information. Accomplishing such a task in a centralized fashion entails great power consumption, congestion at certain nodes, and suffers from robustness issues. A sensible alternative is to compute such projections in a decentralized fashion. To this end, recent works proposed schemes based on graph filters, which compute projections exactly with a finite number of local exchanges among sensor nodes. However, existing methods to obtain these filters are confined to reduced families of projection matrices or small networks. This paper proposes a method tha…