CSSE463: Image Recognition CSSE463: Image Recognition Day 20Day 20

Announcements:Announcements: Sunset detector due Weds. 11:59Sunset detector due Weds. 11:59 Literature reviews due Sunday night 11:59Literature reviews due Sunday night 11:59

Today: Lab for sunset detectorToday: Lab for sunset detector Next week:Next week:

Monday: k-meansMonday: k-means Tuesday: sunset detector labTuesday: sunset detector lab Thursday: template-matchingThursday: template-matching Friday: k-means labFriday: k-means lab

Term Project TeamsTerm Project Teams

1. Photo Mosaic: Ali A, Joe L. Marina K, Daniel N.

2. Where’s Waldo?: Ryohei S, Brandon K, Eric V

3. Stereoscopic Image Depth Mapping: Eric H, Nick K, Laura M, James S

4. Object Tracker: Franklin T, Kyle C, Mike E, Kyle A

5. Detection of Cancer in Brain Scans: Trey C, Nicole R, Katy Y, Maisey T

6. IGVC Vision: Donnie Q, Anders S, Ruffin W, Kurtis Z

7. Paint by Numbers Generator: Ann S, Katie G, Seth T

8. Next Chess Move: Robert W, Andrew M, Eduardo B

Term project next stepsTerm project next steps

Read papers!Read papers!Review what others have done. Review what others have done.

Don’t re-invent the wheel. Don’t re-invent the wheel. Summarize your papersSummarize your papersDueDue

Last words on neural netsLast words on neural nets

Common model of learning Common model of learning machinesmachines

StatisticalLearning (svmtrain)

Labeled TrainingImages

Extract Features(color, texture)

TestImage

Summary

LabelClassifier(svmfwd)

Extract Features(color, texture)

Sunset detector additionSunset detector addition

Please email me a zip file of 10 images Please email me a zip file of 10 images that you think would be tough to classify that you think would be tough to classify by Monday. I’ll compile and send out.by Monday. I’ll compile and send out.

Best if the resolution is 384 x 256 (or Best if the resolution is 384 x 256 (or slightly bigger, but don’t change the aspect slightly bigger, but don’t change the aspect ratio as you rescale)ratio as you rescale)

Sunset ProcessSunset Process Loop over imagesLoop over images

Extract featuresExtract features

NormalizeNormalize Split into train and testSplit into train and test SaveSave Loop over kernel paramsLoop over kernel params

TrainTrain TestTest Record accuracyRecord accuracy

For SVM with param giving For SVM with param giving best accuracy,best accuracy, Generate ROC curveGenerate ROC curve Find good imagesFind good images Do extensionDo extension

Write as you go!Write as you go!