Difference between revisions of "Comparative Morphological Analysis of Brain Structures"
From hpcwiki
(→Data) |
|||
| Line 1: | Line 1: | ||
| − | [[Category:Projects]] | + | |
| + | == People == | ||
| + | |||
| + | * Darwin Martinez | ||
| + | * Hugo Franco | ||
| + | * Francisco Gómez | ||
| + | |||
| + | == Summary == | ||
| + | |||
| + | We propose a novel morphological brain structural characterization method based on relative morphological measures. | ||
| + | |||
| + | == Method overview == | ||
| + | |||
| + | == Data sources == | ||
| + | |||
| + | == Results (Expected) == | ||
| + | |||
| + | * Clinical conference. Morphological changes on dissorder of conscioussness patients. | ||
| + | * Method conference. Initial method description and case study. | ||
| + | * Journal article. Robust experimental study and application to clinical data. | ||
| + | |||
| + | |||
| + | fully automatic framework to detect and extract arbitrary human motion volumes from real-world videos collected from YouTube. Our system is composed of two stages. A person detector is first applied to provide crude information about the possible locations of humans. Then a constrained clustering algorithm groups the detections and rejects false positives based on the appearance similarity and spatio-temporal coherence. In the second stage, we apply a top-down pictorial structure model to complete the extraction of the humans in arbitrary motion. During this procedure, a density propagation technique based on a mixture of Gaussians is employed to propagate temporal information in a principled way. This method reduces greatly the search space for the measurement in the inference stage. We demonstrate the initial success of this framework both quantitatively and qualitatively by using a number of YouTube videos. | ||
| + | |||
| + | <!--[[Category:Projects]] | ||
[[Category:BrainProjects]] | [[Category:BrainProjects]] | ||
''To start editing'' | ''To start editing'' | ||
| Line 16: | Line 40: | ||
== References == | == References == | ||
http://en.wikibooks.org/wiki/SPM/Programming_intro | http://en.wikibooks.org/wiki/SPM/Programming_intro | ||
| + | --!> | ||
Revision as of 11:40, 26 August 2013
Contents |
People
- Darwin Martinez
- Hugo Franco
- Francisco Gómez
Summary
We propose a novel morphological brain structural characterization method based on relative morphological measures.
Method overview
Data sources
Results (Expected)
- Clinical conference. Morphological changes on dissorder of conscioussness patients.
- Method conference. Initial method description and case study.
- Journal article. Robust experimental study and application to clinical data.
fully automatic framework to detect and extract arbitrary human motion volumes from real-world videos collected from YouTube. Our system is composed of two stages. A person detector is first applied to provide crude information about the possible locations of humans. Then a constrained clustering algorithm groups the detections and rejects false positives based on the appearance similarity and spatio-temporal coherence. In the second stage, we apply a top-down pictorial structure model to complete the extraction of the humans in arbitrary motion. During this procedure, a density propagation technique based on a mixture of Gaussians is employed to propagate temporal information in a principled way. This method reduces greatly the search space for the measurement in the inference stage. We demonstrate the initial success of this framework both quantitatively and qualitatively by using a number of YouTube videos.
