SCIEN Talk

Breaking the Barriers to True Augmented Reality [SCIEN]

Topic: 
Breaking the Barriers to True Augmented Reality
Abstract / Description: 

In 1950, Alan Turing introduced the Turing Test, an essential concept in the philosophy of Artificial Intelligence (AI). He proposed an "imitation game" to test the sophistication of an AI software. Similar tests have been suggested for fields including Computer Graphics and Visual Computing. In this talk, we will propose an Augmented Reality Turing Test (ARTT).

Augmented Reality (AR) embeds spatially-registered computer graphics in the user's view in realtime. This capability can be used for a lot of purposes; for example, AR hands can demonstrate manual repair steps to a mechanic. To pass the ARTT, we must create AR objects that are indistinguishable from real objects. Ray Kurzweil bet USD 20,000 that the Turing Test will be passed by 2029. We think that the ARTT can be passed significantly earlier.

We will discuss the grand challenges for passing the ARTT, including: calibration, localization & tracking, modeling, rendering, display technology, and multimodal AR. We will also show examples from our previous and current work at Nara Institute of Science and Technology in Japan.

Date and Time: 
Tuesday, March 14, 2017 - 4:30pm
Venue: 
Clark Center Auditorium

The AR/VR Renaissance: promises, disappointments, unsolved problems [SCIEN]

Topic: 
The AR/VR Renaissance: promises, disappointments, unsolved problems
Abstract / Description: 

Augmented and Virtual Reality have been hailed as "the next big thing" several times in the past 25 years. Some are predicting that VR will be the next computing platform, or at least the next platform for social media. Others worry that today's VR systems are closer to the 1990s Apple Newton than the 2007 Apple iPhone. This talk will feature a short, personal history of AR and VR, a survey of some of current work, sample applications, and remaining problems. Current work with encouraging results include 3D acquisition of dynamic, populated spaces; compact and wide field-of-view AR displays; low-latency and high-dynamic range AR display systems; and AR lightfield displays that may reduce the accommodation-vergence conflict.

More information: http://henryfuchs.web.unc.edu/

Date and Time: 
Wednesday, March 1, 2017 - 4:30pm
Venue: 
Packard 101

First-Photon Imaging and Other Imaging with Few Photons [SCIEN]

Topic: 
First-Photon Imaging and Other Imaging with Few Photons
Abstract / Description: 

LIDAR systems use single-photon detectors to enable long-range reflectivity and depth imaging. By exploiting an inhomoheneous Poisson process observation model and the typical structure of natural scenes, first-photon imaging demonstrates the possibility of accurate LIDAR with only 1 detected photon per pixel, where half of the detections are due to (uninformative) ambient light. I will explain the simple ideas behind first-photon imaging. Then I will touch upon related subsequent works that mitigate the limitations of detector arrays, withstand 25-times more ambient light, allow for unknown ambient light levels, and capture multiple depths per pixel.

Date and Time: 
Wednesday, February 22, 2017 - 4:30pm
Venue: 
Packard 101

Visual Vibration Analysis [SCIEN]

Topic: 
Visual Vibration Analysis
Abstract / Description: 

Davis will show how video can be a powerful way to measure physical vibrations. By relating the frequencies of subtle, often imperceptible changes in video to the vibrations of visible objects, we can reason about the physical properties of those objects and the forces that drive their motion. In my talk I'll show how this can be used to recover sound from silent video (Visual Microphone), estimate the material properties of visible objects (Visual Vibrometry), and learn enough about the physics of objects to create plausible image-space simulations (Dynamic Video).

Date and Time: 
Wednesday, February 15, 2017 - 4:30pm
Venue: 
Packard 101

A Learned Representation for Artistic Style [SCIEN]

Topic: 
A Learned Representation for Artistic Style
Abstract / Description: 

The diversity of painting styles represents a rich visual vocabulary for the construction of an image. The degree to which one may learn and parsimoniously capture this visual vocabulary measures our understanding of the higher level features of paintings, if not images in general. In this work we investigate the construction of a single, scalable deep network that can parsimoniously capture the artistic style of a diversity of paintings. We demonstrate that such a network generalizes across a diversity of artistic styles by reducing a painting to a point in an embedding space. Importantly, this model permits a user to explore new painting styles by arbitrarily combining the styles learned from individual paintings. We hope that this work provides a useful step towards building rich models of paintings and offers a window on to the structure of the learned representation of artistic style.

Date and Time: 
Wednesday, March 8, 2017 - 4:30pm
Venue: 
Packard 101

High-speed imaging meets single-cell analysis [SCIEN]

Topic: 
High-speed imaging meets single-cell analysis
Abstract / Description: 

High-speed imaging is an indispensable tool for blur-free observation and monitoring of fast transient dynamics in today's scientific research, industry, defense, and energy. The field of high-speed imaging has steadily grown since Eadweard Muybridge demonstrated motion-picture photography in 1878. High-speed cameras are commonly used for sports, manufacturing, collision testing, robotic vision, missile tracking, and fusion science and are even available to professional photographers. Over the last few years, high-speed imaging has been shown highly effective for single-cell analysis – the study of individual biological cells among populations for identifying cell-to-cell differences and elucidating cellular heterogeneity invisible to population-averaged measurements. The marriage of these seemingly unrelated disciplines has been made possible by exploiting high-speed imaging's capability of acquiring information-rich images at high frame rates to obtain a snapshot library of numerous cells in a short duration of time (with one cell per frame), which is useful for accurate statistical analysis of the cells. This is a paradigm shift in the field of high-speed imaging since the approach is radically different from its traditional use in slow-motion analysis. In this talk, I introduce a few different methods for high-speed imaging and their application to single-cell analysis for precision medicine and green energy.

Date and Time: 
Friday, January 27, 2017 - 4:30pm
Venue: 
Packard 101

Adversarial perceptual representation learning across diverse modalities and domains [SCIEN]

Topic: 
Adversarial perceptual representation learning across diverse modalities and domains
Abstract / Description: 

Learning of layered or "deep" representations has provided significant advances in computer vision in recent years, but has traditionally been limited to fully supervised settings with very large amounts of training data. New results in adversarial adaptive representation learning show how such methods can also excel when learning in sparse/weakly labeled settings across modalities and domains. I'll review state-of-the-art models for fully convolutional pixel-dense segmentation from weakly labeled input, and will discuss new methods for adapting models to new domains with few or no target labels for categories of interest. As time permits, I'll present recent long-term recurrent network models that learn cross-modal description and explanation, visuomotor robotic policies that adapt to new domains, and deep autonomous driving policies that can be learned from heterogeneous large-scale dashcam video datasets.

Date and Time: 
Wednesday, February 8, 2017 - 4:30pm
Venue: 
Packard 101

Adaptive optics retinal imaging: more than just high-resolution [SCIEN]

Topic: 
Adaptive optics retinal imaging: more than just high-resolution
Abstract / Description: 

The majority of the cells in the retina do not reproduce, making early diagnosing of eye disease paramount. Through improved resolution provided by the correction of the ocular monochromatic aberrations, adaptive optics combined with conventional and novel imaging techniques reveal pathology at the cellular-scale. When compared with existing clinical tools, the ability to visualize retinal cells and microscopic structures non-invasively represents a quantum leap in the potential for diagnosing and managing ocular, systemic and neurological diseases. The presentation will first cover the adaptive optics technology itself and some of its unique technical challenges. This will be followed by a review of AO-enhanced imaging modalities applied to the study of the healthy and diseased eye, with particular focus on multiple-scattering imaging to reveal transparent retinal structures.

Date and Time: 
Wednesday, January 18, 2017 - 4:30pm
Venue: 
Packard 101

Designing and assessing near-eye displays to increase user inclusivity [SCIEN Talk]

Topic: 
Designing and assessing near-eye displays to increase user inclusivity
Abstract / Description: 

Recent years have seen impressive growth in near-eye display systems, which are the basis of most virtual and augmented reality experiences. There are, however, a unique set of challenges to designing a display system that is literally strapped to the user's face. With an estimated half of all adults in the United States requiring some level of visual correction, maximizing inclusivity for near-eye displays is essential. I will describe work that combines principles from optics, optometry, and visual perception to identify and address major limitations of near-eye displays both for users with normal vision and those that require common corrective lenses. I will also describe ongoing work assessing the potential for near-eye displays to assist people with less common visual impairments at performing day-to-day tasks.

Date and Time: 
Wednesday, January 11, 2017 - 4:30pm to 5:15pm
Venue: 
Packard 101

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