Research Presentation by David Whittinghill

My Background Professional software engineer since 1997. Predominantly in research-oriented companies. Domains: Biotechnology Image processing Simulation and modeling More… Master’s of Science, CIT 2004. Thesis: Enterprise Application Development Ph.D. in Computer Graphics Technology, Spring 2009. Thesis: Physically Based Rendering

My Doctoral Research Predictive Rendering experiment. Validate global illumination algorithms. Create a virtual scene modeled on a real world scene. Measure the ambient irradiance levels present in both scenes and store as light maps. Compare the light maps for likeness. A significant match means the algorithms are applicable to scene modeling as well as image production.

Initial Horticulture Experiment Frantz (2003), a horticulture researcher, conducted plant growth chamber experiments. Broader goals: better Advanced Life Support Systems in space missions, cave-grown crops. Placed light sensors in a plant growth chamber. Measured irradiance intensity levels at fixed intervals. Measurements stored as a table; to be converted to a three-dimensional light map.

Light Map A map of the intensities of electromagnetic energy present in a three-dimensional volume. Only interested in wavelengths (λ) between 380 and 750 nanometers.

Virtual Growth Chamber I create a virtual growth chamber modeled after Frantz’ physical one. Measure the virtual light intensities within the volume. Create a map describing the energy distribution in the virtual chamber.

Assembling the Virtual Chamber

Comparison

Comparison

Comparison Δ = 34.10

Comparison Δ = 34.10 Δ = 8.53

Comparison Δ = 34.10 Δ = 8.53 Δ = 27.46

Comparison Δ = Difference between virtual and physical sensors Δ = 34.10 Δ = 8.53 Δ = 27.46

Comparison Δ = Difference between virtual and physical sensors Actual Δ = 34.10 Δ = 8.53 Δ = 27.46

Comparison Δ = Difference between virtual and physical sensors Actual Virtual Δ = 34.10 Δ = 8.53 Δ = 27.46 The smaller the difference between measurements, the better. A smaller delta means the illumination algorithm creates an electromagnetic radiation environment more similar to reality.

Problem Δ = Difference between virtual and physical sensors Actual Virtual Δ = 34.10 Δ = 8.53 Δ = 27.46 Problem: The plants in the virtual and the actual are not identical. Exact duplication is practically impossible! Therefore: observed error between virtual and actual sensors will have high variance.

Solution! Create randomly generated plants that are similar to the actual plant. Take irradiance measurements from each sensor and save. These should now vary. Repeat thousands of times. Collect a range of virtual irradiance observations. Compare the actual observations to the range of virtual observations. Ideally, the actual observations should fall within one or two standard deviations from the mean.

Comparison – Random Plants Net result: a distribution of observations for each sensor Sensor A Sensor B Sensor C Sensor N . . . . . . . .

Analysis For each sensor: Do the actual observations fall within one or two standard deviations of the mean of the virtual observations? Physical Observation Range of Virtual Observations

Implementation Note Used PBRT renderer as base. Very modified. Hand coded in C++: Full spectrum lighting (no RGB) Custom BDF’s SPD and BDF interpolators PBRT Scene generator Plant growth implementation Virtual sensors A LOT of coding!

Scientific Significance Grand Challenges for Engineering National Academy of Engineering Enhance Virtual Reality; improving virtual models of the world.

Scientific Significance Computer Graphics Physically-based rendering algorithms presently used to make convincing/correct images. Will provide evidence that they can be used for virtual spaces as well. A framework for validating algorithms against spaces that are highly shape-variant. A technique for analyzing error between light maps. Applying statistical techniques to analyze global illumination algorithms.

Scientific Significance Horticultural and Climate Science Uniformity studies – can validate uniformity in growth chambers. Plant growth – current design uses fixed BDF, expand this to include dynamic, biologically-derived BDF’s. Predictive growth studies – test if algorithms can predict plant growth patterns in given chamber configurations. 3D Plant volume estimations – currently everything is 2D. Can these findings generalize to underground cave and similar quarantined crops? Model can be expanded to macro levels for climate-level analysis. Currently working with Dr.’s Mitchell and Massa in Horticulture to expand this work even further.

Scientific Significance High Performance Computing (HPC) Each simulation takes several hours to run. Use of HPC resources required to compute several thousand simultaneous simulations. Currently being configured for Condor cluster at PU. Currently consulting with Thomas Hacker in CIT to explore publishing possibilities.

Funding Potential NASA Fundamental Space Biology USDA, NIH The project was originally funded by NASA but was cut due to a shift in political priorities. The Life Sciences portion of NASA’s funding has been restored by President Obama. Highly likely funding for these kinds of projects will be restored as part of those funds. Dr. Mitchell was just passed over on a grant. The reason: not enough predictive validity of light distribution! USDA, NIH This work has strong correlates to crop production. Genetically modified crops can be grown underground, this work could help model those growth environments.

Funding Potential NSF Visual Analytics Cyberinfrastructure Biology Curriculum Development Grants (CCLI, STEM Education)

Other Research Interests Visualization (volume rendering, information visualization, flow visualization) Global illumination Gaming GPGPU Distributed Computing (Enterprise Application Development, Web Apps) High Performance Computing Virtual Reality Mobile Computing Bioinformatics Machine Vision/Robotics

Immediate Research Objectives Light Type, Placement and Automation as Factors Important For Crop Uniformity and Energy Conservation of Controlled Environment Production, 2009. Co-author: Massa, Whittinghill, Bourget, Morrow, Mitchell. Conference: International Symposium on High Technology for Greenhouse System.

Immediate Research Objectives Associating Single Nucleotide Polymorphisms with Binary Traits, 2009. Co-author: Lipka, Whittinghill. I am co-developing the algorithms and providing programming implementation. Target Publication: Genetics. Comparison of Irradiance Distributions Using Isosurface Volume Rendering, 2009. Author. By-product of dissertation work. Target Publications: ISPRS Journal of Photogrammetry and Remote Sensing, Lighting Research & Technology.

Immediate Research Objectives A Framework for Validating Physically Based Rendering, 2009. Author. Directly based off my dissertation’s main thesis. Target Publications: SIGGRAPH, Eurographics. Illumination Map Comparison of Intracanopy Crop Lighting with Simulated Environment Target Publication: HortScience, Eurographics Workshop on Natural Phenomena.

Three Year Outline Year One Two horticulture papers/conferences. Two engineering/CG papers. One bioinformatics paper. Begin mobile graphics book. Visit Harmonix, Zenimax Online. Re-submit NASA Fundamental Space Biology grant with Mitchell lab. Submit Software Engineering grant with US Navy. Aggressively recruit graduate students. Set up gaming institute, gaming internship program. Partner with Microsoft Games for Learning Institute. Serious Games Center with Bill Watson Seek NSF/NIH/USDA funding for light chamber research. Begin constructing course on Enterprise Application Frameworks (Spring, etc.)

Three Year Outline Year Two CG paper (extending algorithmically-based (ABM) reflection models). Three horticulture papers (uniformity, ABM, optimized light placement). SIGGRAPH paper (optimized light placement). Two gaming papers (recruiting, RAD). HPC paper. Finish mobile graphics book. Begin global illumination/PBRT book. Begin enterprise application development book. Continue outreach to gaming companies for student funding. Aggressively recruit graduate students. Expand gaming lab. Focus on applying RAD to gaming. Seek NSF/NIH/USDA funding for light chamber research.

Three Year Outline Year Three One horticulture paper (improved plant’s effect on light). CG paper (optimized light placement). Finish global illumination/PBRT book. Continue enterprise application development book. Paper on Massively Multiplayer Online (MMO) gaming. Aggressively recruit graduate students. Expand gaming lab into online gaming. Seek NSF/NIH/USDA funding for light chamber research.

Departmental Mission …Applied Research… 12 years experience in Research and Development. …educates professional practitioners… I am a professional practitioner! A well-reviewed, effective educator. …develops innovations in the application of emerging technology… Have created and adapted novel implementations that have succeeded in the marketplace.

My Mission To build a meaningful academic career of great achievement and great contribution that is intellectually challenging, spiritually fulfilling, fun, and in service to the pursuit and creation of Knowledge, and the betterment of humanity.