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Events for May 08, 2014

  • PhD Defense - Paul Graham

    Thu, May 08, 2014 @ 10:00 AM - 12:00 PM

    Thomas Lord Department of Computer Science

    University Calendar


    Title:
    A Framework for High-Resolution, High-Fidelity, Inexpensive Facial Scanning

    PhD Candidate: Paul Graham

    Committee:
    Paul Debevec (chair)
    Gerard Medioni
    Michelle Povinelli (outside member)
    Hao Li
    Abhijeet Ghosh


    Abstract:
    We present a framework for high-resolution, high-fidelity, inexpensive facial scanning. The framework combines the speed and cost of passive lighting scanning systems with the fidelity of active lighting systems. The subject is first scanned at the mesoscale, the scale of pores and fine wrinkles. The process is a near-instant method for acquiring facial geometry and reflectance with 24 DSLR cameras and ten flashes. The flashes are fired in rapid succession with subsets of the cameras, which are specially arranged to produce an even distribution of specular highlights on the face. The total capture time is less than the mechanical movement of the eyelid in the human blink reflex. We use this set of acquired images to estimate diffuse color, specular intensity, and surface orientation at each point on the face. With a single photo per camera, we optimize the facial geometry to maximize the consistency of diffuse reflection and minimize the variance of specular highlights using an energy-minimization message-passing technique. This allows the final sub-millimeter surface detail to be obtained via shape-from-specularity, even though every photo is from a different viewpoint. The final system uses commodity components and produces models suitable for generating high-quality digital human characters. The mesostructure is enhanced to include microgeometry through the scanning of skin patches around the face. 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 a different subject with similar skin types. We show that the technique allows for greater realism in facial renderings including a more accurate reproduction of skin's specular reflection effects. A microstructure database is provided for easy cross-subject synthesis during the enhancement stage. Additionally, a multi-view camera calibration technique is introduced. This new technique can be accomplished with a single view from each camera of a cylinder wrapped in a checkerboard pattern. It is fast and resolves extrinsic and intrinsic camera parameters to a sub-pixel re-projection error.

    Location: Henry Salvatori Computer Science Center (SAL) - 322

    Audiences: Everyone Is Invited

    Contact: Lizsl De Leon

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  • PhD Defense - Juan P. Fasola

    Thu, May 08, 2014 @ 02:00 PM - 04:00 PM

    Thomas Lord Department of Computer Science

    University Calendar


    PhD Defense - Juan P. Fasola
    Thursday, May 08, 2014 @ 2:00 PM - 4:00 PM
    RTH 406
    Computer Science

    PhD Candidate: Juan P. Fasola


    Title:

    Socially Assistive and Service Robotics for Older Adults:
    Methodologies for Motivating Exercise and Following Spatial Language Instructions in Discourse


    Committee:
    Maja J Mataric' (chair)
    Gaurav S. Sukhatme
    Aaron Hagedorn (outside member)


    Abstract:
    The growing population of aging adults is increasing the demand for healthcare services worldwide. Socially assistive robotics (SAR) and service robotics have the potential to aid in addressing the needs of the growing elderly population by promoting health benefits, independent living, and improved quality of life. For such robots to become ubiquitous in real-world human environments, they will need to interact with and learn from non-expert users in a manner that is both natural and practical for the users. In particular, such robots will need to be capable of understanding natural language instructions in order to learn new tasks and receive guidance and feedback on task execution.

    Research into SAR and service robotics-based solutions for non-expert users, and in particular older adults, that spans varied assistive tasks generally falls within one of two distinct areas: 1) robot-guided interaction, and 2) user-guided interaction. This dissertation contributes to both of these research areas.

    To address robot-guided interaction, this dissertation presents the design methodology, implementation and evaluation details of a novel SAR approach to motivate and engage elderly users in simple physical exercise. The approach incorporates insights from psychology research into intrinsic motivation and contributes five clear design principles for SAR-based therapeutic interventions. To evaluate the approach and its effectiveness in gaining user acceptance and motivating physical exercise, it was implemented as an integrated system and three user studies were conducted with older adults, to investigate: 1) the effect of praise and relational discourse in the system towards increasing user motivation; 2) the role of user autonomy and choice within the interaction; and 3) the effect of embodiment in the system by comparing user evaluations of similar physically and virtually embodied SAR exercise coaches in addition to evaluating the overall SAR system.

    To address user-guided interactions, specifically with non-expert users through the use of natural language instructions, this dissertation presents a novel methodology that allows service robots to interpret and follow spatial language instructions, with and without user-specified natural language constraints and/or unvoiced pragmatic constraints. This work contributes a general computational framework for the representation of dynamic spatial relations, with both local and global properties. The methodology also contributes a probabilistic approach in the inference of instruction semantics; a general approach for interpreting object pick-and-place tasks; and a novel probabilistic algorithm for the automatic extraction of contextually and semantically valid instruction sequences from unconstrained spatial language discourse, including those containing anaphoric reference expressions. The spatial language interpretation methodology was evaluated in simulation, on two different physical robot platforms, and in a user study conducted with older adults for validation with target users.

    Location: Ronald Tutor Hall of Engineering (RTH) - 406

    Audiences: Everyone Is Invited

    Contact: Lizsl De Leon

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