{"title":"Collaborative filtering of color aesthetics","authors":"Peter O'Donovan, A. Agarwala, Aaron Hertzmann","doi":"10.1145/2630099.2630100","DOIUrl":"https://doi.org/10.1145/2630099.2630100","url":null,"abstract":"This paper investigates individual variation in aesthetic preferences, and learns models for predicting the preferences of individual users. Preferences for color aesthetics are learned using a collaborative filtering approach on a large dataset of rated color themes/palettes. To make predictions, matrix factorization is used to estimate latent vectors for users and color themes. We also propose two extensions to the probabilistic matrix factorization framework. We first describe a feature-based model using learned transformations from feature vectors to a latent space, then extend this model to non-linear transformations using a neural network. These extensions allow our model to predict preferences for color themes not present in the training set. We find that our approach for modelling user preferences outperforms an average aesthetic model which ignores personal variation. We also use the model for measuring theme similarity and visualizing the space of color themes.","PeriodicalId":104077,"journal":{"name":"Proceedings of the Workshop on Computational Aesthetics","volume":"704 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115664950","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Computational rim illumination with aerial robots","authors":"Manohar B. Srikanth, K. Bala, F. Durand","doi":"10.1145/2630099.2630105","DOIUrl":"https://doi.org/10.1145/2630099.2630105","url":null,"abstract":"Lighting plays a major role in photography. Professional photographers use elaborate installations to light their subjects and achieve sophisticated styles. However, lighting moving subjects performing dynamic tasks presents significant challenges and requires expensive manual intervention. A skilled additional assistant might be needed to reposition lights as the subject changes pose or moves, and the extra logistics significantly raises costs and time. We present a new approach to lighting dynamic subjects where an aerial robot equipped with a portable light source lights the subject to automatically achieve a desired lighting effect. We focus on rim lighting, a particularly challenging effect to achieve with dynamic subjects, and allow the photographer to specify a required rim width. Our algorithm processes the images from the photographer's camera and provides necessary motion commands to the aerial robot to achieve the desired rim width in the resulting photographs. We demonstrate a control approach that localizes the aerial robot with reference to the subject and tracks the subject to achieve the necessary motion. Our proof-of-concept results demonstrate the utility of robots in computational lighting.","PeriodicalId":104077,"journal":{"name":"Proceedings of the Workshop on Computational Aesthetics","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127949948","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}