3,325 research outputs found
Robust Head-Pose Estimation Based on Partially-Latent Mixture of Linear Regressions
Head-pose estimation has many applications, such as social event analysis,
human-robot and human-computer interaction, driving assistance, and so forth.
Head-pose estimation is challenging because it must cope with changing
illumination conditions, variabilities in face orientation and in appearance,
partial occlusions of facial landmarks, as well as bounding-box-to-face
alignment errors. We propose tu use a mixture of linear regressions with
partially-latent output. This regression method learns to map high-dimensional
feature vectors (extracted from bounding boxes of faces) onto the joint space
of head-pose angles and bounding-box shifts, such that they are robustly
predicted in the presence of unobservable phenomena. We describe in detail the
mapping method that combines the merits of unsupervised manifold learning
techniques and of mixtures of regressions. We validate our method with three
publicly available datasets and we thoroughly benchmark four variants of the
proposed algorithm with several state-of-the-art head-pose estimation methods.Comment: 12 pages, 5 figures, 3 table
Interactive image segmentation
Segmentation of objects from still images has many practical applications. In the past decade, combinatorial graph cut algorithms have been successfully applied to get fairly accurate object segmentation, along with considerable reduction in the amount of user interaction required. In particular, the Grabcut algorithm has been found to provide satisfactory results for a wide variety of images. This work is an extension to the Grabcut algorithm. The Grabcut algorithm uses Gaussian mixture models to fit the color data. The number of Gaussian components used in mixture model is however fixed. We apply an unsupervised algorithm for estimating the number of Gaussian components to be used for the models. The results obtained show that segmentation accuracy is increased by estimating the Gaussian components required, prior to applying the Grabcut algorithm
A-2000: Close air support aircraft design team
The US Air Force is currently faced with the problem of providing adequate close air support for ground forces. Air response to troops engaged in combat must be rapid and devastating due to the highly fluid battle lines of the future. The A-2000 is the result of a study to design an aircraft to deliver massive fire power accurately. The low cost A-2000 incorporates: large weapons payload; excellent maneuverability; all weather and terrain following capacity; redundant systems; and high survivability
A Bayesian Hyperparameter Inference for Radon-Transformed Image Reconstruction
We develop a
hyperparameter inference method for image
reconstruction from Radon transform
which often appears in the computed tomography, in the manner of
Bayesian inference. Hyperparameters are often introduced in
Bayesian inference to control the strength ratio between prior
information and the fidelity to the observation. Since the quality
of the reconstructed image is controlled by the estimation
accuracy of these hyperparameters, we apply Bayesian inference
into the filtered back-projection (FBP) reconstruction method with
hyperparameters inference and demonstrate that the estimated
hyperparameters can adapt to the noise level in the observation
automatically. In the computer simulation, at first, we show that our
algorithm works well in the model framework environment, that
is, observation noise is an additive white Gaussian noise case. Then,
we also show that our algorithm works well in the more realistic
environment, that is, observation noise is Poissonian noise case.
After that, we demonstrate an application for the real chest CT
image reconstruction under the Gaussian and Poissonian observation
noises
Soft Biometrics: Globally Coherent Solutions for Hair Segmentation and Style Recognition based on Hierarchical MRFs
Markov Random Fields (MRFs) are a populartool in many computer vision problems and faithfully modela broad range of local dependencies. However, rooted in theHammersley-Clifford theorem, they face serious difficulties inenforcing the global coherence of the solutions without using toohigh order cliques that reduce the computational effectiveness ofthe inference phase. Having this problem in mind, we describea multi-layered (hierarchical) architecture for MRFs that isbased exclusively in pairwise connections and typically producesglobally coherent solutions, with 1) one layer working at the local(pixel) level, modelling the interactions between adjacent imagepatches; and 2) a complementary layer working at theobject(hypothesis) level pushing toward globally consistent solutions.During optimization, both layers interact into an equilibriumstate, that not only segments the data, but also classifies it.The proposed MRF architecture is particularly suitable forproblems that deal with biological data (e.g., biometrics), wherethe reasonability of the solutions can be objectively measured.As test case, we considered the problem of hair / facial hairsegmentation and labelling, which are soft biometric labels usefulfor human recognitionin-the-wild. We observed performancelevels close to the state-of-the-art at a much lower computationalcost, both in the segmentation and classification (labelling) tasksinfo:eu-repo/semantics/publishedVersio
Aircraft Modeling and Simulation
Various aerodynamics, structural dynamics, and control design and experimental studies are presented with the aim of advancing green and morphing aircraft research. The results obtained with an in-house CFD code are compared and validated with those of two NASA codes. The aerodynamical model of the UAS-S45 morphing wing as well as the structural model of a morphing winglet are presented. A new design methodology for oleo-pneumatic landing gear drop impact dynamics is presented as well as its experimental validation. The design of a nonlinear dynamic inversion (NDI)-based disturbance rejection control on a tailless aircraft is presented, including its validation using wind tunnel tests
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