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Color Channel Analysis for Improved Image Fitting Method

Enhance image fitting by analyzing color channels for better contrast and stability. Explore using color images instead of grayscale and consider pros and cons of employing different color channels. Implementing in C++ can offer advantages but also present challenges in skin tone detection. Evaluate the impact on fitting precision and processing time.

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Color Channel Analysis for Improved Image Fitting Method

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  1. Fitting til billede Valg af fitting measure – Maximum Gradient • Problemer • Baggrundsstøj • For lav kontrast (pga. konvertering til gråtone)

  2. Nuværende metode – Maximum Gradient Indførsel af threshold for størrelse af gradient. Test • Gik fra 23 til 13 iterationer i fittet til venstre. Andre forbedrings- muligheder • Brug af farve billeder i stedet for gråtone

  3. Analyse af farvekanaler Grå Img Rød Grøn Blå

  4. Analyse af farvekanaler Grå Img Rød Grøn Blå

  5. Analyse af farvekanaler - = Rød Grøn - = Rød Grøn Gøres kun langs normalen i C++ implementation

  6. Fordele/Ulemper ved brug af farvekanaler Fordele • Højere kontrast mellem hånd og baggrund  højere stabilitet ved tracking med skærm som baggrund Ulemper • Meget rødt på skærmen • Problemer med hudfarve  mindre generel implementering. • Mere tidskrævende Eksempel…

  7. Hudfarve som fitting measure Fordele: • Man bliver ikke forstyrret af baggrunden Ulemper: • Folks hudfarve er ikke ens • Hudfarve i baggrunden • Længere evaluerings tid

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