12 research outputs found
Distributed Solution of the Inverse Rig Problem in Blendshape Facial Animation
The problem of rig inversion is central in facial animation as it allows for
a realistic and appealing performance of avatars. With the increasing
complexity of modern blendshape models, execution times increase beyond
practically feasible solutions. A possible approach towards a faster solution
is clustering, which exploits the spacial nature of the face, leading to a
distributed method. In this paper, we go a step further, involving cluster
coupling to get more confident estimates of the overlapping components. Our
algorithm applies the Alternating Direction Method of Multipliers, sharing the
overlapping weights between the subproblems. The results obtained with this
technique show a clear advantage over the naive clustered approach, as measured
in different metrics of success and visual inspection. The method applies to an
arbitrary clustering of the face. We also introduce a novel method for choosing
the number of clusters in a data-free manner. The method tends to find a
clustering such that the resulting clustering graph is sparse but without
losing essential information. Finally, we give a new variant of a data-free
clustering algorithm that produces good scores with respect to the mentioned
strategy for choosing the optimal clustering
High-fidelity Interpretable Inverse Rig: An Accurate and Sparse Solution Optimizing the Quartic Blendshape Model
We propose a method to fit arbitrarily accurate blendshape rig models by
solving the inverse rig problem in realistic human face animation. The method
considers blendshape models with different levels of added corrections and
solves the regularized least-squares problem using coordinate descent, i.e.,
iteratively estimating blendshape weights. Besides making the optimization
easier to solve, this approach ensures that mutually exclusive controllers will
not be activated simultaneously and improves the goodness of fit after each
iteration. We show experimentally that the proposed method yields solutions
with mesh error comparable to or lower than the state-of-the-art approaches
while significantly reducing the cardinality of the weight vector (over 20
percent), hence giving a high-fidelity reconstruction of the reference
expression that is easier to manipulate in the post-production manually. Python
scripts for the algorithm will be publicly available upon acceptance of the
paper
A Majorization-Minimization Based Method for Nonconvex Inverse Rig Problems in Facial Animation: Algorithm Derivation
Automated methods for facial animation are a necessary tool in the modern
industry since the standard blendshape head models consist of hundreds of
controllers and a manual approach is painfully slow. Different solutions have
been proposed that produce output in real-time or generalize well for different
face topologies. However, all these prior works consider a linear approximation
of the blendshape function and hence do not provide a high-enough level of
details for modern realistic human face reconstruction. We build a method for
solving the inverse rig in blendshape animation using quadratic corrective
terms, which increase accuracy. At the same time, due to the proposed
construction of the objective function, it yields a sparser estimated weight
vector compared to the state-of-the-art methods. The former feature means lower
demand for subsequent manual corrections of the solution, while the latter
indicates that the manual modifications are also easier to include. Our
algorithm is iterative and employs a Majorization Minimization paradigm to cope
with the increased complexity produced by adding the corrective terms. The
surrogate function is easy to solve and allows for further parallelization on
the component level within each iteration. This paper is complementary to an
accompanying paper, Rackovi\'c et al. (2023), where we provide detailed
experimental results and discussion, including highly-realistic animation data,
and show a clear superiority of the results compared to the state-of-the-art
methods
Accurate and Interpretable Solution of the Inverse Rig for Realistic Blendshape Models with Quadratic Corrective Terms
We propose a new model-based algorithm solving the inverse rig problem in
facial animation retargeting, exhibiting higher accuracy of the fit and
sparser, more interpretable weight vector compared to SOTA. The proposed method
targets a specific subdomain of human face animation - highly-realistic
blendshape models used in the production of movies and video games. In this
paper, we formulate an optimization problem that takes into account all the
requirements of targeted models. Our objective goes beyond a linear blendshape
model and employs the quadratic corrective terms necessary for correctly
fitting fine details of the mesh. We show that the solution to the proposed
problem yields highly accurate mesh reconstruction even when general-purpose
solvers, like SQP, are used. The results obtained using SQP are highly accurate
in the mesh space but do not exhibit favorable qualities in terms of weight
sparsity and smoothness, and for this reason, we further propose a novel
algorithm relying on a MM technique. The algorithm is specifically suited for
solving the proposed objective, yielding a high-accuracy mesh fit while
respecting the constraints and producing a sparse and smooth set of weights
easy to manipulate and interpret by artists. Our algorithm is benchmarked with
SOTA approaches, and shows an overall superiority of the results, yielding a
smooth animation reconstruction with a relative improvement up to 45 percent in
root mean squared mesh error while keeping the cardinality comparable with
benchmark methods. This paper gives a comprehensive set of evaluation metrics
that cover different aspects of the solution, including mesh accuracy, sparsity
of the weights, and smoothness of the animation curves, as well as the
appearance of the produced animation, which human experts evaluated
MRI reconstruction using Markov random field and total variation as composite prior
Reconstruction of magnetic resonance images (MRI) benefits from incorporating a priori knowledge about statistical dependencies among the representation coefficients. Recent results demonstrate that modeling intraband dependencies with Markov Random Field (MRF) models enable superior reconstructions compared to inter-scale models. In this paper, we develop a novel reconstruction method, which includes a composite prior based on an MRF model and Total Variation (TV). We use an anisotropic MRF model and propose an original data-driven method for the adaptive estimation of its parameters. From a Bayesian perspective, we define a new position-dependent type of regularization and derive a compact reconstruction algorithm with a novel soft-thresholding rule. Experimental results show the effectiveness of this method compared to the state of the art in the field
Oksidacija antrahinonskih boja peroksidazom iz rena imobilisanom u obliku umreženih enzimskih agregata
Finding a sustainable and ecofriendly methods for recalcitrant synthetic dyes removal is a researchers major challenge. A carrier-free technique for commercial HRP immobilization is a focus of the present study. The immobilized biocatalyst, HRP-CLEAs with 580 U g-1 of the activity was obtained under the following immobilization conditions: precipitation reagent 80% ammonium sulphate, cross-linking reagent 1% of glutaraldehyde and protein-fedder, bovine serum albumin (BSA) concentration 5 mg ml-1. The obtained HRP-CLEAs showed great affinity towards model anthraquinone dye, C. I. Acid Violet 109. 88.4% of the dye was oxidized under the reaction conditions: pH 4, dye concentration 40 mg l-1, H2O2 concentration 1 mM and 0.1 U of HRP-CLEAs. The possibility of the immobilized biocatalyst application in five and eight oxidation cycles of the dye and pyrogallol (retained activity 80%), respectively, indicates that HRP-CLEAs is an efficient and environmentally friendly biocatalyst with great potential in aromatic compounds removal from wastewater. This paper is a continuation of our earlier research related to HRP from horseradish extract immobilization in the form of CLEAs and the application in the wastewater colored with a synthetic anthraquinone dye treatment.Pronalazak održivih i ekoloÅ”ki prihvatljivih metoda za uklanjanje sintetiÄkih boja je jedan od vodeÄih izazova za istraživaÄe. U ovom radu akcenat je na metodi imobilizacije bez primene nosaÄa. Imobilisani preparat peroksidaze iz rena, aktivnosti 580 U g-1 dobijen je pod sledeÄim uslovima imobilizacije: taložni reagens 80% amonijum-sulfat, umrežavajuÄi reagens 1% glutaraldehid i goveÄi serum albumin koncentracije 5 mg ml-1. Dobijeni umreženi agregat peroksidaze iz rena pokazao je veliki afinitet prema model antrahinonskoj boji, C. I. AV 109. Pod optimalnim uslovima: pH 4, koncentracja boje 40 mg-1, koncentracija H2O2 i 0,1 U enzimske aktivnosti oksidovano je 88,4% ispitivane boje. MoguÄnost primene imobilisanog enzima kroz pet i osam uzastopnih ciklusa oksidacije boje i pirogalola (zadržana aktivnost 80%) pokazuje da je imobilisani enzim efikasan i ekoloÅ”ki prihvatljiv biokatalizator koji se može koristiti u oksidaciji aromatiÄnih jedinjenja iz otpadnih voda. Ovaj rad predstavlja nastavak istraživanja vezanog za umrežavanje peroksidaze iz svežeg ekstrakta rena, koja se takoÄe pokazala kao imobilisani biokatalizator sa velikim potencijalom primene u tretmanu obojenih otpadnih voda
Immobilization of horseradish peroxidase onto Purolite (R) A109 and its anthraquinone dye biodegradation and detoxification potential
Horseradish peroxidase (HRP) is a highly specific enzyme with great potential for use in the decolorization of synthetic dyes. A comprehensive study of HRP immobilization using various techniques such as adsorption and covalent immobilization on the novel carrier Purolite (R) A109 with a special focus on enzymatic decolorization and toxicity of artificially colored wastewater. The immobilized preparations with an activity of 156.21 +/- 1.41 U g(-1) and 85.71 +/- 1.62 U g(-1) after the HRP adsorption and covalent immobilization, respectively, were obtained. Stability and reusability of the immobilized preparations were also evaluated. A noteworthy decolorization level (similar to 90%) with immobilized HRP was achieved. Phytotoxicity testing using Mung bean seeds and acute toxicity assay with Artemia salina has confirmed the applicability of the obtained immobilized preparation in industrial wastewater plants for the treatment of colored wastewater
Synthesis of Aliphatic Esters of Cinnamic Acid as Potential Lipophilic Antioxidants Catalyzed by Lipase B from Candida antarctica
Immobilized lipase from Candida antarctica (Novozyme 435) was tested for the synthesis of various phenolic acid esters (ethyl and n-butyl cinnamate, ethyl p-coumarate and n-butyl p-methoxycinnamate). The second-order kinetic model was used to mathematically describe the reaction kinetics and to compare present processes quantitatively. It was found that the model agreed well with the experimental data. Further, the effect of alcohol type on the esterification of cinnamic acid was investigated. The immobilized lipase showed more ability to catalyze the synthesis of butyl cinnamate. Therefore, the process was optimized for the synthesis of butyl cinnamate as a function of solvent polarity (logP) and amount of biocatalyst. The highest ester yield of 60.7 % was obtained for the highest enzyme concentration tested (3 % w/w), but the productivity was for 34 % lower than the corresponding value obtained for the enzyme concentration of 1 % (w/w). The synthesized esters were purified, identified, and screened for antioxidant activities. Both DPPH assay and cyclic voltammetry measurement have shown that cinnamic acid esters have better antioxidant properties than cinnamic acid itself