Thesis Progress
I completed the design for the instance model. The instance model will be built based on an initial detection and segmentation using the boundary-fragment base model (which is already implemented). Color image patches will be extracted from the segmented image and clustered in the manner of Leibe and Lebo’s implicit shape models. A color correlation function will be used for the clustering distance function, and patches will be selected using the Harris corner detector. In addition, the instance model will include a global appearance factor, represented in a color histogram of the entire segmentation mask. This information will be joined with the base model.
The detection procedure will begin with the base model and instance model performing detection in parallel, in their typical boundary-fragment and implicit-shape manners. The unclustered Hough space votes will be combined (with appropriate weights) and clustered using mean-shift to find a detection. The graph cut algorithm will be used for segmentation. Its “boundary” term will be calculated from the backprojected boundary fragment parts and the image’s edge transform. The “region” term will be generated from a combination of the backprojected instance model parts and the correlation of each pixel with the color histogram.
Diagrams of the design: training and detection/segmentation.
Most of the instance model’s components are already implemented, including the color correlation, color histogram, interest point and patch extraction, clustering, voting, and mean-shift algorithms. The work remaining is to assemble these components into the actual model and modify the graph cut segmentation code.
Chapter 1 of the thesis report is finished, with figures added and “to-do” notes completed. I also began work on chapter 2 and updated existing text to reflect the final design decisions.
I also laid out a detailed plan for all of the remaining work.
This week, I plan to finish chapter two and implement the training portion of the instance model. After that, the detection/segmentation code, testing, and remaining chapters of the report are all that remain.