Using more clean motorbike data

Previously, I had used 20 training images for parameter estimations of the location and appearance models. I re-ran the tests with 47 training images of motorbikes (sans background clutter). I then ran the recognition procedure on 10 different test images consisting of motorbikes, cars and faces.




The results were as follows:

CombinedLogProb =

-249.1764
-233.0733
-226.2195
-293.5680
-257.1131
-304.4388
-284.6287
-251.9015
-254.5245
-297.4117

>> LogProbApp

LogProbApp =

-141.6296
-118.7043
-118.2580
-179.9357
-138.6968
-186.3235
-162.7556
-110.6465
-137.2324
-161.1289

>> LogProbLoc

LogProbLoc =

-107.5468
-114.3690
-107.9615
-113.6323
-118.4163
-118.1153
-121.8730
-141.2551
-117.2921
-136.2827

Images 1-4 were bikes, 5-7 were cars, 8-9 were faces and 10 was another bike.