The Digital Survivor of Sexual Assault (DS2A) is an interface that allows a user to have a conversational experience with a survivor of sexual assault, using Artificial Intelligence technology and recorded videos. The application uses a statistical classifier to retrieve contextually appropriate pre-recorded video utterances by the survivor, together with dialogue management policies which enable users to conduct simulated conversations with the survivor about the sexual assault, its aftermath, and other pertinent topics. The content in the application has been specifically elicited to support the needs for the training of U.S. Army professionals in the Sexual Harassment/Assault Response and Prevention (SHARP) Program, and the application comes with an instructional support package. The system has been tested with approximately 200 users, and is presently being used in the SHARP Academy's capstone course.

We present a learning-based approach for synthesizing facial geometry at medium and fine scales from diffusely-lit facial texture maps. When applied to an image sequence, the synthesized detail is temporally coherent. Unlike current state-of-the-art methods [17, 5], which assume "dark is deep", our model is trained with measured facial detail collected using polarized gradient illumination in a Light Stage [20]. This enables us to produce plausible facial detail across the entire face, including where previous approaches may incorrectly interpret dark features as concavities such as at moles, hair stubble, and occluded pores. Instead of directly inferring 3D geometry, we propose to encode fine details in high-resolution displacement maps which are learned through a hybrid network adopting the state-of-the-art image-to-image translation network [29] and super resolution network [43]. To effectively capture geometric detail at both mid- and high frequencies, we factorize the learning into two separate sub-networks, enabling the full range of facial detail to be modeled. Results from our learning-based approach compare favorably with a high-quality active facial scanhening technique, and require only a single passive lighting condition without a complex scanning setup.

We present a multi-view stereo reconstruction technique that directly produces a complete high-fidelity head model with consistent facial mesh topology. While existing techniques decouple shape estimation and facial tracking, our framework jointly optimizes for stereo constraints and consistent mesh parameterization. Our method is therefore free from drift and fully parallelizable for dynamic facial performance capture. We produce highly detailed facial geometries with artist-quality UV parameterization, including secondary elements such as eyeballs, mouth pockets, nostrils, and the back of the head. Our approach consists of deforming a common template model to match multi-view input images of the subject, while satisfying cross-view, cross-subject, and cross-pose consistencies using a combination of 2D landmark detection, optical flow, and surface and volumetric Laplacian regularization. Since the flow is never computed between frames, our method is trivially parallelized by processing each frame independently. Accurate rigid head pose is extracted using a PCA-based dimension reduction and denoising scheme. We demonstrate high-fidelity performance capture results with challenging head motion and complex facial expressions around eye and mouth regions. While the quality of our results is on par with the current state-of-the-art, our approach can be fully parallelized, does not suffer from drift, and produces face models with production-quality mesh topologies.

We present a practical framework for reproducing omnidirectional incident illumination conditions with complex spectra using a light stage with multispectral LED lights. For lighting acquisition, we augment standard RGB panoramic photography with one or more observations of a color chart with numerous reflectance spectra. We then solve for how to drive the multispectral light sources so that they best reproduce the appearance of the color charts in the original lighting. Even when solving for non-negative intensities, we show that accurate lighting reproduction is achievable using just four or six distinct LED spectra for a wide range of incident illumination spectra. A significant benefit of our approach is that it does not require the use of specialized equipment (other than the light stage) such as monochromators, spectroradiometers, or explicit knowledge of the LED power spectra, camera spectral response functions, or color chart reflectance spectra. We describe two simple devices for multispectral lighting capture, one for slow measurements of detailed angular spectral detail, and one for fast measurements with coarse angular detail. We validate the approach by realistically compositing real subjects into acquired lighting environments, showing accurate matches to how the subject would actually look within the environments, even for those including complex multispectral illumination. We also demonstrate dynamic lighting capture and playback using the technique.

Time-offset interaction is a new technology that allows for two-way communication with a person who is not available for conversation in real time: a large set of statements are prepared in advance, and users access these statements through natural conversation that mimics face-to-face interaction. Conversational reactions to user questions are retrieved through a statistical classifier, using technology that is similar to previous interactive systems with synthetic characters; however, all of the retrieved utterances are genuine statements by a real person. Recordings of answers, listening and idle behaviors, and blending techniques are used to create a persistent visual image of the person throughout the interaction. A proof-of-concept has been implemented using the likeness of Pinchas Gutter, a Holocaust survivor, enabling short conversations about his family, his religious views, and resistance. This proof-of-concept has been shown to dozens of people, from school children to Holocaust scholars, with many commenting on the impact of the experience and potential for this kind of interface.

We present a process for rendering a realistic facial performance with control of viewpoint and illumination. The performance is based on one or more high-quality geometry and reflectance scans of an actor in static poses, driven by one or more video streams of a performance. We compute optical flow correspondences between neighboring video frames, and a sparse set of correspondences between static scans and video frames. The latter are made possible by leveraging the relightability of the static 3D scans to match the viewpoint(s) and appearance of the actor in videos taken in arbitrary environments. As optical flow tends to compute proper correspondence for some areas but not others, we also compute a smoothed, per-pixel confidence map for every computed flow, based on normalized cross-correlation. These flows and their confidences yield a set of weighted triangulation constraints among the static poses and the frames of a performance. Given a single artist-prepared face mesh for one static pose, we optimally combine the weighted triangulation constraints, along with a shape regularization term, into a consistent 3D geometry solution over the entire performance that is drift free by construction. In contrast to previous work, even partial correspondences contribute to drift minimization, for example, where a successful match is found in the eye region but not the mouth. Our shape regularization employs a differential shape term based on a spatially varying blend of the differential shapes of the static poses and neighboring dynamic poses, weighted by the associated flow confidences. These weights also permit dynamic reflectance maps to be produced for the performance by blending the static scan maps. Finally, as the geometry and maps are represented on a consistent artist-friendly mesh, we render the resulting high-quality animated face geometry and animated reflectance maps using standard rendering tools.

Abstract We present a technique for generating microstructure‐level facial geometry by augmenting a mesostructure‐level facial scan with detail synthesized from a set of exemplar skin patches scanned at much higher resolution. Additionally, we make point‐source reflectance measurements of the skin patches to characterize the specular reflectance lobes at this smaller scale and analyze facial reflectance variation at both the mesostructure and microstructure scales. We digitize the exemplar patches with a polarization‐based computational illumination technique which considers specular reflection and single scattering. The recorded microstructure patches can be used to synthesize full‐facial microstructure detail for either the same subject or to a different subject. We show that the technique allows for greater realism in facial renderings including more accurate reproduction of skin's specular reflection effects.

We present a set of algorithms and an associated display system capable of producing correctly rendered eye contact between a three-dimensionally transmitted remote participant and a group of observers in a 3D teleconferencing system. The participant's face is scanned in 3D at 30Hz and transmitted in real time to an autostereoscopic horizontal-parallax 3D display, displaying him or her over more than a 180° field of view observable to multiple observers. To render the geometry with correct perspective, we create a fast vertex shader based on a 6D lookup table for projecting 3D scene vertices to a range of subject angles, heights, and distances. We generalize the projection mathematics to arbitrarily shaped display surfaces, which allows us to employ a curved concave display surface to focus the high speed imagery to individual observers. To achieve two-way eye contact, we capture 2D video from a cross-polarized camera reflected to the position of the virtual participant's eyes, and display this 2D video feed on a large screen in front of the real participant, replicating the viewpoint of their virtual self. To achieve correct vertical perspective, we further leverage this image to track the position of each audience member's eyes, allowing the 3D display to render correct vertical perspective for each of the viewers around the device. The result is a one-to-many 3D teleconferencing system able to reproduce the effects of gaze, attention, and eye contact generally missing in traditional teleconferencing systems.

We present a novel method for acquisition, modeling, compression, and synthesis of realistic facial deformations using polynomial displacement maps. Our method consists of an analysis phase where the relationship between motion capture markers and detailed facial geometry is inferred, and a synthesis phase where novel detailed animated facial geometry is driven solely by a sparse set of motion capture markers. For analysis, we record the actor wearing facial markers while performing a set of training expression clips. We capture real-time high-resolution facial deformations, including dynamic wrinkle and pore detail, using interleaved structured light 3D scanning and photometric stereo. Next, we compute displacements between a neutral mesh driven by the motion capture markers and the high-resolution captured expressions. These geometric displacements are stored in a polynomial displacement map which is parameterized according to the local deformations of the motion capture dots. For synthesis, we drive the polynomial displacement map with new motion capture data. This allows the recreation of large-scale muscle deformation, medium and fine wrinkles, and dynamic skin pore detail. Applications include the compression of existing performance data and the synthesis of new performances. Our technique is independent of the underlying geometry capture system and can be used to automatically generate high-frequency wrinkle and pore details on top of many existing facial animation systems.

We describe a set of rendering techniques for an autostereoscopic light field display able to present interactive 3D graphics to multiple simultaneous viewers 360 degrees around the display. The display consists of a high-speed video projector, a spinning mirror covered by a holographic diffuser, and FPGA circuitry to decode specially rendered DVI video signals. The display uses a standard programmable graphics card to render over 5,000 images per second of interactive 3D graphics, projecting 360-degree views with 1.25 degree separation up to 20 updates per second. We describe the system's projection geometry and its calibration process, and we present a multiple-center-of-projection rendering technique for creating perspective-correct images from arbitrary viewpoints around the display. Our projection technique allows correct vertical perspective and parallax to be rendered for any height and distance when these parameters are known, and we demonstrate this effect with interactive raster graphics using a tracking system to measure the viewer's height and distance. We further apply our projection technique to the display of photographed light fields with accurate horizontal and vertical parallax. We conclude with a discussion of the display's visual accommodation performance and discuss techniques for displaying color imagery.

No abstract available.