Structure and Aesthetics in Non-Photorealistic Images Hua Li, David Mould, and Jim Davies Carleton University

Artistic or Messed 2/35

Related Work on Evaluating Non-Photorealistic Algorithms Performance based on processing speed ill-suited for stylization Side-by-side comparisons not fully convinced by audience 3/35

Perceptual Evaluation on Non-Photorealistic Algorithms Quantitative evaluation rating scores [Schumann et al. 96, Gooch and Willemsen 02, Mandryk et al. 2011, Mould et al. 2012] response time [Gooch et al. 04] eye-tracking data [Mandryk et al. 2011, Mould et al. 2012] Qualitative evaluation questionnaire-based 4/35

Motivation of Our Study Tone  Structure Tone-based Structure-based Halftoning [Pang et al. 08] [Chang et al. 09] [Ours 10] Stippling [Secord 02] [Mould 07] [Martin et al. 11] [Ours 11] Screening [Ulichney 98] Abstraction [Kyprianidis 11] [Mould 12, 13] [Floyd and Steinberg 76] [Ostromoukhov 01] [Qu et al. 08] [Ours 11] 5/35

Questions to Answer Are structural and aesthetic quality related? Do images matter for side-by-side comparisons? 6/35

Participants 30 participants 15 female and 15 male 11 artists aged 18 to 33 7/35

Study Overview 1 ~ 1.5 hours to complete the experiment Using the keyboard or the mouse to enter their responses Tasks: rating structural and aesthetic quality collecting response times for rendered images 8/35

Image Stimuli Seven categories include cars, cats, persons, flowers, buildings, mugs, and birds. Each category contains 13 different images including one unprocessed image and 12 rendered images using 12 algorithms. Images are black and white, or greyscale to remove the influence of color. 9/36

Procedure Step 1: verbal introduction Step 2: training Step 3: formal study Step 4: questionnaire Step 5: ranking 10/35

Interfaces Used 11/35 Interface for collecting the response time

Interfaces Used Aesthetic rating Structural rating 12/35

Experimental Images -Bird Category Unprocessed 13/35

Experimental Images - Bird Category Structure-Aware Structure-Preserving Stippling (SPS) 14/35

Experimental Images - Bird Category Structure-Aware Content-Sensitive Screening (CSS) 15/35

Experimental Images - Bird Category Structure-Aware SPS with Exclusion Masks (SPH) 16/35

Experimental Images - Bird Category Structure-Aware Line Art using edge tangent field (ETF) 17/35

Experimental Images - Bird Category Structure-Aware Artistic Tessellation (AT) 18/35

Experimental Images - Bird Category Structure-Aware Line Art from SPS (Drawing) 19/35

Experimental Images - Bird Category Tone-based Secord’s Stippling Method (Secord) 20/35

Experimental Images - Bird Category Tone-based Line Art using edge tangent field (Mmosaics) 21/35

Experimental Images - Bird Category Contrast-Aware Halftoning (CAH) 22/35

Experimental Images - Bird Category Black and White (BW) 23/35

Experimental Images - Bird Category Reduced Information Adding 50% salt and pepper noise (Noisy) 24/35

Experimental Images - Bird Category Reduced Information Gaussian filter (Blurring) 25/35

Positive Correlation Between Structural and Aesthetic Ratings 26/35

Dot-based Methods (Stippling) Tone-based Structure-Aware Structure-Aware Tone-based 27/35

Region-based Methods (Mosaics) Tone-based Structure-Aware Structure-Aware Tone-based 28/35

Effect of Category on Ratings 29/35

Effect of Category on Response Time Building < Flower < Bird < Cat < Person < Mug < Car 30/35

Artists and Non-Artists 31/35

Overall Ranks after Study Participants preferred the AT images (7/30 responses) the most, CAH second (6/30). Participants’ least favorite blurred images most often (20/30 responses), and with AT second (5/30). Controversial ranking for stylized images rendered by the AT method. 32/35

Conclusions Considering structure as a possible way to increase aesthetic appeal. Considering the choice of the images used. Generally, bird images were the easiest images to abstract, while Person images were the most difficult. 33/35

Future Work More Participants More Categories More NPR Algorithms Eye tracker 34/35

Thanks for Your Attention. Questions? 35/35

Effect of Algorithms on Ratings (skip) 36/41

Effect of Algorithms on Response Time (skip) 37/41

Interaction between Categories and Algorithms (skip) Aesthetic scores 38/41

Interaction between Categories and Algorithms (skip) 39/41

Interaction between Categories and Algorithms (skip) 40/41