Estimasi Citra Kedalaman Dengan Conditional Random Field (CRF) dan Structured Support Vector Machine (SSVM)
DOI:
https://doi.org/10.29207/resti.v1i3.64Keywords:
Conditional Random Field, Structured Support Vector Machine, Depth ImageAbstract
Autonomous UAVs typically require systems capable of mapping (segmenting) the region of a colored image. Regional segmentation will be used to determine the existence of obstacles. Segmentation in an image initiated by grouping a number of pixels by color and proximity, with superpixel. Furthermore, the characteristics of each segmented region were extracted using Principal Component Analysis (PCA). Sequential segregation is a process of introducing a region that requires chain information obtained from the introduction before and after it called stochastic process. Solving this is done using Structured Support Vector Machines (SSVM). Meanwhile, to determine the weight in SSVM required a Conditional Random Field (CRF) model. The results show a good accuracy in the segmentation of the region that is 71%.
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