Abstract Computer‐based technology has played a significant role in crime prevention over the past 30 years, especially with the popularization of spatial databases and crime mapping systems. Police departments frequently use hotspot analysis to identify regions that should be a priority in receiving preventive resources. Practitioners and researchers agree that tracking crime over time and identifying its geographic patterns are vital information for planning efficiently. Frequently, police departments have access to systems that are too complicated and excessively technical, leading to modest usage. By working closely together with domain experts from police agencies of two different countries, we identified and characterized five domain tasks inherent to the hotspot analysis problem and developed SHOC, a visualization tool that strives for simplicity and ease of use in helping users to perform all the domain tasks. SHOC is included in a visual analytics system that allows users without technical expertise to annotate, save, and share analyses. We also demonstrate that our system effectively supports the completion of the domain tasks in two different real‐world case studies.

Most recent crowd simulation algorithms equip agents with a synthetic vision component for steering. They offer promising perspectives through a more realistic simulation of the way humans navigate according to their perception of the surrounding environment. In this paper, we propose a new perception/motion loop to steering agents along collision free trajectories that significantly improves the quality of vision-based crowd simulators. In contrast with solutions where agents avoid collisions in a purely reactive (binary) way, we suggest exploring the full range of possible adaptations and retaining the locally optimal one. To this end, we introduce a cost function, based on perceptual variables, which estimates an agent's situation considering both the risks of future collision and a desired destination. We then compute the partial derivatives of that function with respect to all possible motion adaptations. The agent then adapts its motion by following the gradient. This paper has thus two main contributions: the definition of a general purpose control scheme for steering synthetic vision-based agents; and the proposition of cost functions for evaluating the perceived danger of the current situation. We demonstrate improvements in several cases.

Abstract Physically based characters have not yet received wide adoption in the entertainment industry because control remains both difficult and unreliable. Even with the incorporation of motion capture for reference, which adds believability, characters fail to be convincing in their appearance when the control is not robust. To address these issues, we propose a simple Jacobian transpose torque controller that employs virtual actuators to create a fast and reasonable tracking system for motion capture. We combine this controller with a novel approach we call the topple‐free foot strategy which conservatively applies artificial torques to the standing foot to produce a character that is capable of performing with arbitrary robustness. The system is both easy to implement and straightforward for the animator to adjust to the desired robustness, by considering the trade‐off between physical realism and stability. We showcase the benefit of our system with a wide variety of example simulations, including energetic motions with multiple support contact changes, such as capoeira, as well as an extension that highlights the approach coupled with a Simbicon controlled walker. With this work, we aim to advance the state‐of‐the‐art in the practical design for physically based characters that can employ unaltered reference motion (e.g. motion capture data) and directly adapt it to a simulated environment without the need for optimization or inverse dynamics.

We develop a technique that achieves a plausible three-dimensional aged facial model of a missing person. It uses simulated diploid reproduction in which a three-dimensional aged model of a missing person is carefully modeled considering the geometrical traits of her parents. The genetic characteristics of both parents, stored into their genomic datastructures, are used to construct pools of male and female gametes for simulated fecundation. A plausible model of the missing person is selected among the generated descendants and its genomic data structure is saved. The parents' models and data structures are updated to reflect the age of the missing person at search time. Next, the genomic data structure of the missing person is updated with the information contained in the parents' updated data structure, and an updated plausible model of the missing person is generated. Case studies are presented that demonstrate the potentials of the proposed methodology.

Control for physically based characters presents a challenging task because it requires not only the management of the functional aspects that lead to the successful completion of the desired task, but also the resulting movement must be visually appealing and meet the quality requirements of the application. Crafting controllers to generate desirable behaviors is difficult because the specification of the final outcome is indirect and often at odds with the functional control of the task. This paper presents a method which exploits the natural modal vibrations of a physically based character in order to provide a palette of basis coordinations that animators can use to assemble their desired motion. A visual user interface allows an animator to guide the final outcome by selecting and inhibiting the use of specific modes. Then, an optimization routine applies the user-chosen modes in the tuning of parameters for a fixed locomotion control structure. The result is an animation system that is easy for an animator to drive and is able to produce a wide variety of locomotion styles for varying character morphologies.

Nowadays, applications of virtual reality (VR) and computer games use human characters models with ever-increasing sophistication. Additional challenges are posed by applications, such as life-simulation computer games (The Sims, Spore, etc.), internet-based virtual worlds (Second Life) and animation movies, that require simulation of kinship and interaction between isolated populations with well defined ethnic characteristics. The main difficulty in those situations is to generate models automatically, which are physically similar to a given population or family. In this paper, human reproduction is mimicked to produce character models, which inherit genetic characteristics from their ancestors. Unlike morphing techniques, in our method, it is possible that a genetic characteristic from an ancestor be manifested only after a few generations.