Learning to Generate Posters of Scientific Papers

Researchers often summarize their work in the form of posters. Posters provide a coherent and efficient way to convey core ideas from scientific papers. Generating a good scientific poster, however, is a complex and time consuming cognitive task, since such posters need to be readable, informative, and visually aesthetic. In this paper, for the first time, we study the challenging problem of learning to generate posters from scientific papers. To this end, a data-driven framework, that utilizes graphical models, is proposed. Specifically, given content to display, the key elements of a good poster, including panel layout and attributes of each panel, are learned and inferred from data. Then, given inferred layout and attributes, composition of graphical elements within each panel is synthesized. To learn and validate our model, we collect and make public a Poster-Paper dataset, which consists of scientific papers and corresponding posters with exhaustively labelled panels and attributes. Qualitative and quantitative results indicate the effectiveness of our approach.Comment: in Proceedings of the 30th AAAI Conference on Artificial Intelligence (AAAI'16), Phoenix, AZ, 201

Optimisation of automatic variable graphic layout and imposition

Prednosti automatizacije u grafičkoj pripremi primarno leže u povećanju efikasnosti u produkciji pripreme za tisak i montaže, posebice u poslovima koji se ponavljaju. Ostale prednosti su smanjivanje troškova pošto se više posla može odraditi s manje zaposlenika. Jedan od načina izrade automatizacije je i skriptiranje. Mogu se izvršavati kratke skripte koje odrađuju samo jedan zadatak, kompleksne skripte koje obavljaju višestruke zadatke, pa sve do onih koje automatiziraju cijeli izdavački proces. Kod skripti koje obavljaju kompleksne zadatke vrijeme izvršavanja može biti dugotrajno. U radu je opisana skripta koja ostvaruje automatizaciju izrade varijabilne grafičke pripreme, montaže i numeriranja za digitalni tisak. Kvantitativno su određene dobivena automatizacija i ušteda u vremenu korištenjem automatiziranog procesa. Osim učinkom automatizacije na stvarni proces grafičke pripreme ovaj rad bavi se i optimizacijom napisane skripte kako bi se skratilo vrijeme njezinog izvršavanja i utvrdili čimbenici koji utječu na skriptna vremena.The benefit of automation in graphic prepress lies primarily in an increase of efficiency in the production of layout and imposition of repetitive tasks by shortening lead time. Another benefit is cost reduction, since more work can be done with fewer staff members. One way of automating is by using scripts. Scripts can be written to execute just one task, complex scripts can perform multiple tasks and some scripts automate the entire publishing process. With scripts that execute complex tasks execution period can be time consuming. This paper describes the script that was made to automate variable data layout, imposition and to number digital printing. Quantitative research was carried out in this paper to determine achieved automation and time reduction by using automated processes. This paper also deals with written script optimization in order to shorten the time of its execution and to identify factors that affect the script execution time

Epitomize Your Photos

With the rapid growth of digital photography, sharing of photos with friends and family has become very popular. When people share their photos, they usually organize them in albums according to events or places. To tell the story of some important events in one's life, it is desirable to have an efficient summarization tool which can help people to receive a quick overview of an album containing huge number of photos. In this paper, we present and analyze an approach for photo album summarization through a novel social game ``Epitome'' as a Facebook application. This social game can collect research data and, at the same time, it provides a collage or a cover photo of the user's photo album, while the user enjoys playing the game. The proof of concept of the proposed method is demonstrated through a set of experiments on several photo albums. As a benchmark comparison to this game, we perform automatic visual analysis considering several state-of-the-art features. We also evaluate the usability of the game by making use of a questionnaire on several subjects who played "Epitome" game. Furthermore, we address privacy issues concerning shared photos in Facebook applications

Object Duplicate Detection

With the technological evolution of digital acquisition and storage technologies, millions of images and video sequences are captured every day and shared in online services. One way of exploring this huge volume of images and videos is through searching a particular object depicted in images or videos by making use of object duplicate detection. Therefore, need of research on object duplicate detection is validated by several image and video retrieval applications, such as tag propagation, augmented reality, surveillance, mobile visual search, and television statistic measurement. Object duplicate detection is detecting visually same or very similar object to a query. Input is not restricted to an image, it can be several images from an object or even it can be a video. This dissertation describes the author's contribution to solve problems on object duplicate detection in computer vision. A novel graph-based approach is introduced for 2D and 3D object duplicate detection in still images. Graph model is used to represent the 3D spatial information of the object based on the local features extracted from training images so that an explicit and complex 3D object modeling is avoided. Therefore, improved performance can be achieved in comparison to existing methods in terms of both robustness and computational complexity. Our method is shown to be robust in detecting the same objects even when images containing the objects are taken from very different viewpoints or distances. Furthermore, we apply our object duplicate detection method to video, where the training images are added iteratively to the video sequence in order to compensate for 3D view variations, illumination changes and partial occlusions. Finally, we show several mobile applications for object duplicate detection, such as object recognition based museum guide, money recognition or flower recognition. General object duplicate detection may fail to detection chess figures, however considering context, like chess board position and height of the chess figure, detection can be more accurate. We show that user interaction further improves image retrieval compared to pure content-based methods through a game, called Epitome