Zobrazeno 1 - 10
of 12
pro vyhledávání: '"Shawn Recker"'
Publikováno v:
AIPR
A common trade-off among object detection algorithms is accuracy-for-speed (or vice versa). To meet our application’s real-time requirement, we use a Single Shot MultiBox Detector (SSD) model. This architecture meets our latency requirements; howev
Publikováno v:
AIPR
We discuss the precision autonomous landing features of the Joint Tactical Aerial Resupply Vehicle (JTARV) platform. Autonomous navigation for aerial vehicles demands that computer vision algorithms provide not only relevant, actionable information,
Autor:
John D. Owens, Connie S. Nguyen, Kenneth I. Joy, Mikhail M. Shashkov, Shawn Recker, Jason Mak
Publikováno v:
AIPR
We introduce a method for creating very dense reconstructions of datasets, particularly turn-table varieties. The method takes in initial reconstructions (of any origin) and makes them denser by interpolating depth values in two-dimensional image spa
Publikováno v:
Journal of Graphics, GPU, and Game Tools. 14:31-56
Despite nearly universal support for the IEEE 754 floating-point standard on modern general-purpose processors, a wide variety of more specialized processors do not provide hardware floating-point units and rely instead on integer-only pipelines. Ray
Publikováno v:
Computer Vision-ACCV 2014 Workshops ISBN: 9783319166278
ACCV Workshops (1)
ACCV Workshops (1)
The angular error-based triangulation method and the parallax path method are both high-performance methods for large-scale multi-view sequential reconstruction that can be parallelized on the GPU. We map parallax paths to the GPU and test its perfor
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d80e0be55a426bd01e5f1d2072855370
https://doi.org/10.1007/978-3-319-16628-5_19
https://doi.org/10.1007/978-3-319-16628-5_19
Autor:
Mario Yepez, Kenneth I. Joy, Mikhail M. Shashkov, Shawn Recker, Christiaan Gribble, Mauricio Hess-Flores
Publikováno v:
AIPR
Recker, Shawn; Gribble, Christiaan; Shashkov, Mikhail; Yepez, Mario; Hess-Flores, Mauricio; & Joy, Kenneth I.Recker, Shawn; & Hess-Flores, Mauricio eds. (2014). Depth Data Assisted Structure-from-Motion Parameter Optimization and Feature Track Correction. UC Davis: Institute for Data Analysis and Visualization. Retrieved from: http://www.escholarship.org/uc/item/2j6708m4
Recker, Shawn; Gribble, Christiaan; Shashkov, Mikhail; Yepez, Mario; Hess-Flores, Mauricio; & Joy, Kenneth I.Recker, Shawn; & Hess-Flores, Mauricio eds. (2014). Depth Data Assisted Structure-from-Motion Parameter Optimization and Feature Track Correction. UC Davis: Institute for Data Analysis and Visualization. Retrieved from: http://www.escholarship.org/uc/item/2j6708m4
Structure-from-Motion (SfM) applications attempt to reconstruct the three-dimensional (3D) geometry of an underlying scene from a collection of images, taken from various camera viewpoints. Traditional optimization techniques in SfM, which compute an
Publikováno v:
ICPR
Hess-Flores, Mauricio; Recker, Shawn; & Joy, Kenneth I.Hess-Flores, Mauricio ed. (2014). Uncertainty, Baseline, and Noise Analysis for L1 Error-Based Multi-View Triangulation. UC Davis: Institute for Data Analysis and Visualization. Retrieved from: http://www.escholarship.org/uc/item/6nk233jn
Hess-Flores, Mauricio; Recker, Shawn; & Joy, Kenneth I.Hess-Flores, Mauricio ed. (2014). Uncertainty, Baseline, and Noise Analysis for L1 Error-Based Multi-View Triangulation. UC Davis: Institute for Data Analysis and Visualization. Retrieved from: http://www.escholarship.org/uc/item/6nk233jn
A comprehensive uncertainty, baseline, and noise analysis in computing 3D points using a recent L1-based triangulation algorithm is presented. This method is shown to be not only faster and more accurate than its main competitor, linear triangulation
Publikováno v:
WACV
Mak, Jason; Hess-Flores, Mauricio; Recker, Shawn; Owens, John D.; & Joy, Kenneth I.Mak, Jason; & Hess-Flores, Mauricio eds. (2014). GPU-Accelerated and Efficient Multi-View Triangulation for Scene Reconstruction. UC Davis: Institute for Data Analysis and Visualization. Retrieved from: http://www.escholarship.org/uc/item/5jj6z2qr
Mak, Jason; Hess-Flores, Mauricio; Recker, Sean; Owens, John D; & Joy, Kenneth I. (2014). GPU-Accelerated and Efficient Multi-View Triangulation for Scene Reconstruction. IEEE Winter Conference on Applications of Computer Vision (WACV) 2014. UC Davis: Retrieved from: http://www.escholarship.org/uc/item/4nf4n0bc
Mak, Jason; Hess-Flores, Mauricio; Recker, Shawn; Owens, John D.; & Joy, Kenneth I.Mak, Jason; & Hess-Flores, Mauricio eds. (2014). GPU-Accelerated and Efficient Multi-View Triangulation for Scene Reconstruction. UC Davis: Institute for Data Analysis and Visualization. Retrieved from: http://www.escholarship.org/uc/item/5jj6z2qr
Mak, Jason; Hess-Flores, Mauricio; Recker, Sean; Owens, John D; & Joy, Kenneth I. (2014). GPU-Accelerated and Efficient Multi-View Triangulation for Scene Reconstruction. IEEE Winter Conference on Applications of Computer Vision (WACV) 2014. UC Davis: Retrieved from: http://www.escholarship.org/uc/item/4nf4n0bc
This paper presents a framework for GPU-accelerated N-view triangulation in multi-view reconstruction that improves processing time and final reprojection error with respect to methods in the literature. The framework uses an algorithm based on optim
Publikováno v:
ICCV Workshops
This paper presents a novel framework for practical and accurate N-view triangulation of scene points. The algorithm is based on applying swarm optimization inside a robustly-computed bounding box, using an angular error-based L1 cost function which
Publikováno v:
AIPR
Analyzing sources and causes of error in multi-view scene reconstruction is difficult. In the absence of any ground-truth information, reprojection error is the only valid metric to assess error. Unfortunately, inspecting reprojection error values do