Localized statistical models in computer visionReportar como inadecuado

Localized statistical models in computer vision

Localized statistical models in computer vision - Descarga este documento en PDF. Documentación en PDF para descargar gratis. Disponible también para leer online.

Computer vision approximates human vision using computers. Two subsets are explored in this work: image segmentation and visual tracking. Segmentation involves partitioning an image into logical parts, and tracking analyzes objects as they change over time.The presented research explores a key hypothesis: localizing analysis of visual information can improve the accuracy of segmentation and tracking results. Accordingly, a new class of segmentation techniques based on localized analysis is developed and explored. Next, these techniques are applied to two challenging problems: neuron bundle segmentation in diffusion tensor imagery DTI and plaque detection in computed tomography angiography CTA imagery. Experiments demonstrate that local analysis is well suited for these medical imaging tasks. Finally, a visual tracking algorithm is shown that uses temporal localization to track objects that change drastically over time.

Georgia Tech Theses and Dissertations - School of Electrical and Computer Engineering Theses and Dissertations -

Autor: Lankton, Shawn M. - -

Fuente: https://smartech.gatech.edu/

Documentos relacionados