street cat photo booth: isea2016 work-in-progress
TRANSCRIPT
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Street Cat Photo Booth
Machine Learning,Disembodied Practice,& Curious Cats
Leigh M. Smith, leighsmith.com, LANDR Jordan Matthew Yerman, The Street Cat Project
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+ = ?
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Automation:● Raspberry Pi 2 + Camera +
IR.● IR Sensor controls image
capture.● 5 sec. sample interval.● Images are queued for eval.● Accepted images uploaded
to Instagram.● Web server displays progress
and sets # tags.● TODO: Robust Geotagging.
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● Uses a sliding window over the captured image.● Histogram of Oriented Gradients (HOG) forms the
low-level features.● Gradients fed into a Support Vector Machine (SVM)
machine learning algorithm.● Binary classify combinations of gradients →
detector.● Identifies the number of faces in each image.● Must be trained on a dataset of images that have
cat faces at similar image distance to the booth.● Trained 272, tested 1407 images, recall = 0.504.
Cat Face Recognition:
“Why must I feel like that? Why must I map the cat? Nothin’ but the HOG in me!”(apologies to George Clinton)
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Street Cat Photo Booth:#CatWalks
ISEA 2016 香港 #CatWalk:19th May, 9am
Alleyway Entrance:Nanking St at Reclamation St(MTR: Jordan)
Map: search Twitter, Facebook for #ISEA2016 #CatWalk
Tokyo 東京 2016 #CatWalk:Higashi-Ikebukuro Central Park (Metro: Higashi-Ikebukuro)May 26, early afternoon TBD
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Instagram: @streetcatphotoboothFacebook: The Street Cat Project
LeighSmith.comJordanMatthewYerman.com
#ISEA2016 # 猫