Cognitive Modeling for Computer Animation: A Comparative Review

Cognitive modeling is a provocative new paradigm that paves the way towards intelligent graphical characters by providing them with logic and reasoning skills. Cognitively empowered self-animating characters will see in the near future a widespread use in the interactive game, multimedia, virtual reality and production animation industries. This review covers three recently-published papers from the field of cognitive modeling for computer animation. The approaches and techniques employed are very different. The cognition model in the first paper is built on top of Soar, which is intended as a general cognitive architecture for developing systems that exhibit intelligent behaviors. The second paper uses an active plan tree and a plan library to achieve the fast and robust reactivity to the environment changes. The third paper, based on an AI formalism known as the situation calculus, develops a cognitive modeling language called CML and uses it to specify a behavior outline or sketch plan to direct the characters in terms of goals. Instead of presenting each paper in isolation then comparatively analyzing them, we take a top-down approach by first classifying the field into three different categories and then attempting to put each paper into a proper category. Hopefully in this way it can provide a more cohesive, systematic view of cognitive modeling approaches employed in computer animation

Dynamics of the sub-Ohmic spin-boson model: a time-dependent variational study

The Dirac-Frenkel time-dependent variation is employed to probe the dynamics of the zero temperature sub-Ohmic spin-boson model with strong friction utilizing the Davydov D1 ansatz. It is shown that initial conditions of the phonon bath have considerable influence on the dynamics. Counterintuitively, even in the very strong coupling regime, quantum coherence features still manage to survive under the polarized bath initial condition, while such features are absent under the factorized bath initial condition. In addition, a coherent-incoherent transition is found at a critical coupling strength alpha ~ 0.1 for s=0.25 under the factorized bath initial condition. We quantify how faithfully our ansatz follows the Schr\"{o}dinger equation, finding that the time-dependent variational approach is robust for strong dissipation and deep sub-Ohmic baths (s<<1).Comment: 8 pages, 6 figure

Sub-Ohmic spin-boson model with off-diagonal coupling: Ground state properties

We have carried out analytical and numerical studies of the spin-boson model in the sub-ohmic regime with the influence of both the diagonal and off-diagonal coupling accounted for via the Davydov D1 variational ansatz. While a second-order phase transition is known to be exhibited by this model in the presence of diagonal coupling only, we demonstrate the emergence of a discontinuous first order phase transition upon incorporation of the off-diagonal coupling. A plot of the ground state energy versus magnetization highlights the discontinuous nature of the transition between the isotropic (zero magnetization) state and nematic (finite magnetization) phases. We have also calculated the entanglement entropy and a discontinuity found at a critical coupling strength further supports the discontinuous crossover in the spin-boson model in the presence of off-diagonal coupling. It is further revealed via a canonical transformation approach that for the special case of identical exponents for the spectral densities of the diagonal and the off-diagonal coupling, there exists a continuous crossover from a single localized phase to doubly degenerate localized phase with differing magnetizations.Comment: 11 pages, 7 figure

Entanglement dynamics of a two-qubit system coupled individually to Ohmic baths

Developed originally for the Holstein polaron, the Davydov D1 ansatz is an efficient, yet extremely accurate trial state for time-dependent variation of the spin-boson model [J. Chem. Phys. 138, 084111 (2013)]. In this work, the Dirac-Frenkel time-dependent variational procedure utilizing the Davydov D1 ansatz is implemented to study entanglement dynamics of two qubits under the influence of two independent baths. The Ohmic spectral density is used without the Born-Markov approximation or the rotating-wave approximation. In the strong coupling regime finite-time disentanglement is always found to exist, while at the intermediate coupling regime, the entanglement dynamics calculated by Davydov D1 ansatz displays oscillatory behavior in addition to entanglement disappearance and revival.Comment: 8 pages, 3 figure

Dynamic And Quantitative Radiomics Analysis In Interventional Radiology

Interventional Radiology (IR) is a subspecialty of radiology that performs invasive procedures driven by diagnostic imaging for predictive and therapeutic purpose. The development of artificial intelligence (AI) has revolutionized the industry of IR. Researchers have created sophisticated models backed by machine learning algorithms and optimization methodologies for image registration, cellular structure detection and computer-aided disease diagnosis and prognosis predictions. However, due to the incapacity of the human eye to detect tiny structural characteristics and inter-radiologist heterogeneity, conventional experience-based IR visual evaluations may have drawbacks. Radiomics, a technique that utilizes machine learning, offers a practical and quantifiable solution to this issue. This technology has been used to evaluate the heterogeneity of malignancies that are difficult to detect by the human eye by creating an automated pipeline for the extraction and analysis of high throughput computational imaging characteristics from radiological medical pictures. However, it is a demanding task to directly put radiomics into applications in IR because of the heterogeneity and complexity of medical imaging data. Furthermore, recent radiomics studies are based on static images, while many clinical applications (such as detecting the occurrence and development of tumors and assessing patient response to chemotherapy and immunotherapy) is a dynamic process. Merely incorporating static features cannot comprehensively reflect the metabolic characteristics and dynamic processes of tumors or soft tissues. To address these issues, we proposed a robust feature selection framework to manage the high-dimensional small-size data. Apart from that, we explore and propose a descriptor in the view of computer vision and physiology by integrating static radiomics features with time-varying information in tumor dynamics. The major contributions to this study include: Firstly, we construct a result-driven feature selection framework, which could efficiently reduce the dimension of the original feature set. The framework integrates different feature selection techniques to ensure the distinctiveness, uniqueness, and generalization ability of the output feature set. In the task of classification hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (ICC) in primary liver cancer, only three radiomics features (chosen from more than 1, 800 features of the proposed framework) can obtain an AUC of 0.83 in the independent dataset. Besides, we also analyze features’ pattern and contributions to the results, enhancing clinical interpretability of radiomics biomarkers. Secondly, we explore and build a pulmonary perfusion descriptor based on 18F-FDG whole-body dynamic PET images. Our major novelties include: 1) propose a physiology-and-computer-vision-interpretable descriptor construction framework by the decomposition of spatiotemporal information into three dimensions: shades of grey levels, textures, and dynamics. 2) The spatio-temporal comparison of pulmonary descriptor intra and inter patients is feasible, making it possible to be an auxiliary diagnostic tool in pulmonary function assessment. 3) Compared with traditional PET metabolic biomarker analysis, the proposed descriptor incorporates image’s temporal information, which enables a better understanding of the time-various mechanisms and detection of visual perfusion abnormalities among different patients. 4) The proposed descriptor eliminates the impact of vascular branching structure and gravity effect by utilizing time warping algorithms. Our experimental results showed that our proposed framework and descriptor are promising tools to medical imaging analysis

Design of a Virtual Human Presenter

We created a virtual human presenter based on extensions to the JackTM animated agent system. Inputs to the presenter system are in the form of speech texts with embedded commands, most of which relate to the virtual presenter\u27s body language. The system then makes him act as a presenter with presentation skills in real-time 3D animation synchronized with speech outputs. He can make presentations with virtual visual aids, with virtual 3D environments, or even on the WWW