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Events for June 07, 2019

  • Repeating EventMeet USC: Admission Presentation, Campus Tour, and Engineering Talk

    Fri, Jun 07, 2019

    Viterbi School of Engineering Undergraduate Admission

    Workshops & Infosessions

    This half day program is designed for prospective freshmen (HS juniors and younger) and family members. Meet USC includes an information session on the University and the Admission process, a student led walking tour of campus, and a meeting with us in the Viterbi School. During the engineering session we will discuss the curriculum, research opportunities, hands-on projects, entrepreneurial support programs, and other aspects of the engineering school. Meet USC is designed to answer all of your questions about USC, the application process, and financial aid.

    Reservations are required for Meet USC. This program occurs twice, once at 8:30 a.m. and again at 12:30 p.m.

    Please make sure to check availability and register online for the session you wish to attend. Also, remember to list an Engineering major as your \"intended major\" on the webform!


    Location: Ronald Tutor Campus Center (TCC) - USC Admission Office

    Audiences: Everyone Is Invited

    View All Dates

    Contact: Viterbi Admission

  • Repeating EventSix Sigma Black Belt

    Fri, Jun 07, 2019 @ 09:00 AM - 05:00 PM

    Executive Education

    Conferences, Lectures, & Seminars

    Abstract: Week 1: June 4-7, 2019
    Week 2: July 15-19, 2019
    Week 3: August 5-9, 2019
    9am - 5pm

    Learn the advanced problem-solving skills you need to implement the principles, practices, and techniques of Six Sigma to maximize performance and cost reductions in your organization. During this three-week practitioner course, you will learn how to measure a process, analyze the results, develop process improvements, and quantify the resulting savings. You will be required to complete a project demonstrating mastery of appropriate analytical methods and pass an examination to earn Six Sigma Black Belt Certificate. This practitioner course for Six Sigma implementation provides extensive coverage of the Six Sigma process, as well as intensive exposure to the key analytical tools associated with Six Sigma, including project management, team skills, cost analysis, FMEA, basic statistics, inferential statistics, sampling, goodness of fit testing, regression and correlation analysis, reliability, design of experiments, statistical process control, measurement systems analysis, and simulation. Computer applications are emphasized.

    NOTE: Participants must provide a windows based computer running Microsoft Office to the seminar.

    More Info: https://viterbiexeced.usc.edu/engineering-program-areas/six-sigma-lean-certification/six-sigma-black-belt/

    Audiences: Registered Attendees

    View All Dates

    Contact: Corporate & Professional Programs

    Event Link: https://viterbiexeced.usc.edu/engineering-program-areas/six-sigma-lean-certification/six-sigma-black-belt/

  • PhD Defense - Chloe LeGendre

    Fri, Jun 07, 2019 @ 02:00 PM - 03:30 PM

    Thomas Lord Department of Computer Science

    University Calendar

    PhD Candidate: Chloe LeGendre
    Committee: Paul Debevec (CS, chair), Jernej Barbic (CS), Michael Fink (Cinema)
    Title: Compositing Real and Virtual Objects with Realistic, Color-Accurate Illumination
    Room: GFS 104
    Time: June 7 (Friday) 2:00 PM - 3:30 PM

    In digital compositing, images from a variety of sources are combined to form a seamless, realistic result that appears as though it could have been photographed in the real world. This technique is extensively used in visual effects and film production, for example when an actor filmed in a studio is composited into a different real or virtual environment. It is also widely used in augmented or mixed reality, where rendered virtual imagery is combined with a live video feed. For a realistic and convincing composite, the content from the various source images must appear to have been captured at the same time under the same lighting conditions. Thus, whether such content is photographed or synthetically rendered, digital compositing benefits from accurate measurement of scene illumination, and, for rendered objects, also from accurate material reflectance measurement. In this dissertation, we therefore present new techniques for the measurement and estimation of illumination and reflectance, geared towards the goal of producing realistic and color-accurate digital composites.

    First, we present a multispectral illumination measurement and playback technique to extend studio lighting reproduction for live-action compositing to the multispectral domain, improving color rendition as compared with previous work. Next, a theoretical analysis affords the selection of an optimal, minimal set of light emitting diodes (LEDs) of distinct spectra for this technique. For post-production methods, we extend image-based relighting to the multispectral domain for the same goal of improved color rendition, forming the appearance of an object in a novel lighting environment by combining images of the object as lit by an omnidirectional, multispectral lighting basis. For the specific application of digitizing humans, which enables rendering a person under a novel viewpoint or lighting environment, we also present an efficient approach to multispectral high-resolution facial scanning using monochrome cameras, where both geometric resolution and color rendition are improved compared to previous work.

    The final technique we present is a machine learning based method to estimate high dynamic range (HDR), omnidirectional illumination given only a single, unconstrained mobile phone image with a limited field-of-view. As image formation using the aforementioned post-production techniques requires accurate lighting measurement, typically realized using panoramic HDR photography and a special color calibration target, real-time mobile mixed reality compositing with convincing illumination remains elusive because these off-line light measurement techniques are both impractical and not accessible for the average mobile phone user. Our learning based approach for omnidirectional HDR lighting estimation from a single image is the first to generalize to both indoor and outdoor scenes, while comparing favorably to previous methods developed to handle only a single class of lighting.

    Location: Grace Ford Salvatori Hall Of Letters, Arts & Sciences (GFS) - 104

    Audiences: Everyone Is Invited

    Contact: Lizsl De Leon