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Business Identification:Spatial Detection
Alexander DarinoWeek 5
2
Outline
• Recap of Previous Work• Business Name Detection• Business Name Matching• Business Spatial Detection• Weaknesses to Current Approach• Alternatives to Current Approach• Acknowledgements
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Outline
LatitudeLongitude
Geocoding
ReverseGeocoding
Nearby Businesses
Image OCR Detected Text
Business Name
Matching
BusinessIdentification
Business Spatial
Detection
Week 4 Week 5
Previous Work
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Image Where Am I? Latitude, Longitude
Latitude, Longitude
Geocoding
ReverseGeocoding
Nearby Businesses
65George S Aiken CoWinghart's Burger & Whiskey BarMarket SquareBella Sera On the SquareChipotleNOLALas Velas…
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Business Name Detection
LatitudeLongitude
Geocoding
ReverseGeocoding
Nearby Businesses
Image OCR Detected Text
Business Name
Matching
BusinessIdentification
Business Spatial
Detection
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Business Name Detection
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Business Name Detection…<line dy="95" dx="1573" y="420" x="11" value="1">
<space dy="26" dx="9" y="379" x="11"/> <box dy="26" dx="9" y="379" x="11" value="0" weights="96" numac="1"/> <box dy="25" dx="6" y="406" x="11" value="J" weights="98,62" numac="2"
achars="p"/> <box dy="19" dx="5" y="382" x="19" value="n" weights="96" numac="1"/> <space dy="5" dx="30" y="441" x="25"/> <box dy="5" dx="7" y="441" x="56" value="."/> <box dy="24" dx="5" y="401" x="57" value="."/> <box dy="13" dx="8" y="429" x="58" value="v" weights="98" numac="1"/> <box dy="26" dx="9" y="402" x="60" value="." weights="94" numac="1"/> <box dy="22" dx="5" y="406" x="67" value="0" weights="96" numac="1"/> <box dy="10" dx="12" y="444" x="71" value="."/>
</line>…
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Business Name Matching
LatitudeLongitude
Geocoding
ReverseGeocoding
Nearby Businesses
Image OCR Detected Text
Business Name
Matching
BusinessIdentification
Business Spatial
Detection
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Business Name Matching
• Developed Confidence Attribution Algorithm– Confidence of OCR Token being Name Token• Example: Confidence of “ESTUANT” representing
“RESTAURANT”• Point-based system
– Confidence of Name appearing in Image• Sum of points of matching OCR Text• Use logarithmically-normalized points to determine
business inclusion threshold
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Business Name Matching
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Business Name Matching
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Business Name Matching
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Business Name Matching
Note: k is usually 2 or 3
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Business Name Matching
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Business Name Matching
Note: This originally did not appear because it did not exceed the confidence threshold. It now appears because it contributes to the Business Name Identification
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Business Spatial Identification
LatitudeLongitude
Geocoding
ReverseGeocoding
Nearby Businesses
Image OCR Detected Text
Business Name
Matching
BusinessIdentification
Business Spatial
Detection
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Business Spatial Identification
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Business Spatial Identification
Aiken George S Co
Category:Food, GroceryAddress: 218 Forbes AvePittsburgh, PA 15222Phone: (412) 391-6358Rating: 4.5/5 (2 Reviews)
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Business Spatial Identification
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Business Spatial Identification
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Business Spatial Identification
Bruegger's Bagels
Category:BagelsAddress: Market Sq
Pittsburgh, PA 15222Phone: (412) 281-2515Rating: Not Rated
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Weaknesses to Current Approach
LatitudeLongitude
Geocoding
ReverseGeocoding
Nearby Businesses
Image OCR Detected Text
Business Name
Matching
BusinessIdentification
Business Spatial
Detection
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Weaknesses to Current Approach
Lots of Garbage
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Weaknesses to Current Approach
Fragmented Word Detection
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Weaknesses to Current ApproachFails with
non-orthogonal perspective
Did I already mention lots of
garbage?
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Weaknesses to Current Approach
Fails withnon-roman text
Not scale-invariant
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ALTERNATIVE APPROACHESTwo different
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Alternative #1: Image Matching
LatitudeLongitude
Geocoding
ReverseGeocoding
Nearby Businesses
Image
Match to Storefront
Image
BusinessIdentification
Business Spatial
Detection
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Alternative #1: Image Matching
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Alternative #1: Image Matching
• Weaknesses– Storefront images aren’t always available for
matching– Computationally Expensive• Hundreds of images to compare to
– Nothing new– Boring!
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Alternative #2: Template Matching
LatitudeLongitude
Geocoding
ReverseGeocoding
Nearby Businesses
Image
Render Templates of Business Names in Different Fonts
Business SpatialDetection
Image Matching(eg. SIFT, HAAR)
Template Images
Business Identification
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Alternative #2: Template Matching
• Tambellini• Tambellini• Tambellini• Tambellini
• Tambellini• Tambellini• Tambellini• Tambellini
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Alternative #2: Template Matching
OCR• Not Scale Invariant• Unbounded Search• Fragmented Recognition• Roman-only font
Alternative #2• Scale Invariant• Bounded Search• Whole-word recognition• All fonts
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Acknowledgements
• Subh– Provided several ideas regarding template
matching using SIFT, HAAR features, etc
Thank You
