Object Detection and 3D Modeling · screened Poisson surface reconstruction to create a 3D model....
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Object Detection and 3D Modeling Mentor(s): Murali Subbarao Ananth Rajan 3D Modeling of Indoor Scenes -A 180-degree view of an indoor scene was captured and combined using the Iterative Closest Point algorithm to produce a combined point-cloud. -The combined point-cloud was sampled with 30,000 points and reconstituted using screened Poisson surface reconstruction to create a 3D model. Social Impact -This technology has many possible applications such as cartography, law enforcement, Augmented Reality, and video game design. It has the possibility of creating a space for simulating realistic indoor conditions for educational/research purposes. Background -The Intel Realsense D435 Camera has an integrated stereo depth and RGB sensor that allows perspective to be added to an image frame. -Realsense Viewer allows simultaneous RGB-D capture. -Combined RBG and depth data is displayed In point-cloud format for processing. -A point-cloud was sampled using Poisson Disk Sampling to reduce noise and improve clarity of generated 3D model. Project Team Name: i3 2D Applications -Face detection and feature recognition was implemented using cascade object detection -Object recognition using pretrained AlexNet neural network allows common objects to be classified. -Panoramic stitching using feature-based image registration Special thanks to Professor Murali Subbarao for guiding me through this project. Glossary Point-cloud- A set of points in 3D space RGB-D – Red, Green, Blue, Depth data
Transcript of Object Detection and 3D Modeling · screened Poisson surface reconstruction to create a 3D model....
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Electrical and Computer Engineering
Object Detection and 3D Modeling
Mentor(s): Murali SubbaraoAnanth Rajan
3D Modeling of Indoor Scenes
-A 180-degree view of an indoor scene was captured and combined using the Iterative Closest Point algorithm toproduce a combined point-cloud.
-The combined point-cloud was sampledwith 30,000 points and reconstituted usingscreened Poisson surface reconstruction to create a 3D model.
Social Impact
-This technology has many possibleapplications such as cartography, lawenforcement, Augmented Reality, and videogame design. It has the possibility ofcreating a space for simulating realisticindoor conditions for educational/researchpurposes.
Background
-The Intel Realsense D435Camera has an integrated stereo depth and RGB sensor that allowsperspective to be added to an image frame.
-Realsense Viewerallows simultaneousRGB-D capture.
-Combined RBG and depth data isdisplayed In point-cloud format forprocessing.
-A point-cloud was sampled using PoissonDisk Sampling to reduce noise and improve clarity of generated 3D model.
Project Team Name: i3
2D Applications
-Face detection and featurerecognition was implemented using cascade object detection
-Object recognition using pretrained AlexNet neuralnetwork allows common objects to be classified.
-Panoramic stitchingusing feature-basedimage registration
Special thanks to Professor Murali Subbarao for guiding me through this project.
Glossary
Point-cloud- A set of points in 3D spaceRGB-D – Red, Green, Blue, Depth data
![Points2Surf · 2020. 8. 2. · comparisons to Screened Poisson Reconstruction (SPR) [19] in Section4. Data-driven surface reconstruction. Recently, several methods have been proposed](https://static.fdocuments.us/doc/165x107/60668ff91c670e0de017da25/2020-8-2-comparisons-to-screened-poisson-reconstruction-spr-19-in-section4.jpg)
![Photorealistic Style Transfer with Screened Poisson Equation ...MECHREZ et al.: SCREENED POISSON FOR PHOTOREALISTIC STYLE TRANSFER 3 gain in this task. Gatys et al. [10] transfer style](https://static.fdocuments.us/doc/165x107/5ff5bf9338a9c15e025eada7/photorealistic-style-transfer-with-screened-poisson-equation-mechrez-et-al.jpg)
