setting up some naive car tracking
implementing basic structure of the tracking example
walking through image IDs
finding detectionDetails indices per image
space for max sliding-window match for each pair of filters
walking through all pairs of bboxes for each pair of images
hmm, conv2 wants double instead of single
ah, forgot that off-the-shelf conv2 won't work for matching filters -- doing a pile of conv2's instead
implemented matlab conv2 with depth. probably slow, but we're just comparing detected filters instead of comparing with the whole image.
explanining logic in corr2_withDepth. (oh, and renamed conv2_withDepth -> corr2_withDepth)
correlation seems to work. (havent tested carefully, but results don't look too crazy). I should decide some conventions on local vs. global indexing of bboxes. I'm kind of jumbling these together at the moment.
next steps: put indices of maxes from matchScores into matches(). [can use that Matlab argmax trick.] also, should try running this on some sort of car tracking challenge dataset