Hotels-50K: A Global Hotel Recognition Dataset

Recognizing a hotel from an image of a hotel room is important for human trafficking investigations. Images directly link victims to places and can help verify where victims have been trafficked, and where their traffickers might move them or others in the future. Recognizing the hotel from images is challenging because of low image quality, uncommon camera perspectives, large occlusions (often the victim), and the similarity of objects (e.g., furniture, art, bedding) across different hotel rooms. To support efforts towards this hotel recognition task, we have curated a dataset of over 1 million annotated hotel room images from 50,000 hotels. These images include professionally captured photographs from travel websites and crowd-sourced images from a mobile application, which are more similar to the types of images analyzed in real-world investigations. We present a baseline approach based on a standard network architecture and a collection of data-augmentation approaches tuned to this problem domain

Advertising Health Status in Male Sex Workers\u27 Online Ads

This brief report examines whether male sex workers mentioned any health concerns in their online ads. The analysis uses 203 male escorts\u27 online ads collected from America Online chat rooms in 2001/2002. The results indicate that only 25 percent of male escorts explicitly mentioned any health-related words or phrases in their ads. The results also show that whether a male escort mentioned health in their ad is correlated with the type of images they would like to portray and with the type of sex services they offer

Birth room images: What they tell us about childbirth. A discourse analysis of birth rooms in developed countries

© 2016 Elsevier Ltd. Objective: this study examined images of birth rooms in developed countries to analyse the messages and visual discourse being communicated through images. Design: a small qualitative study using Kress and van Leeuwen's (2006) social semiotic theoretical framework for image analysis, a form of discourse analysis. Setting/participants: forty images of birth rooms were collected in 2013 from Google Images, Flickr, Wikimedia Commons and midwifery colleagues. The images were from obstetric units, alongside and freestanding midwifery units located in developed countries (Australia, Canada, Europe, New Zealand, United Kingdom and the United States of America). Main findings: findings demonstrated three kinds of birth room images; the technological, the 'homelike', and the hybrid domesticated birth room. The most dominant was the technological birth room, with a focus on the labour bed and medical equipment. The visual messages from images of the technological birth room reinforce the notion that the bed is the most appropriate place to give birth and the use of medical equipment is intrinsically involved in the birth process. Childbirth is thus construed as risky/dangerous. Key conclusions and implications for practice: as images on the Internet inform and persuade society about stereotypical behaviours, the trends of our time and sociocultural norms, it is important to recognise images of the technological birth room on the Internet may be influential in dictating women's attitudes, choices and behaviour, before they enter the birth room

Fine-To-Coarse Global Registration of RGB-D Scans

RGB-D scanning of indoor environments is important for many applications, including real estate, interior design, and virtual reality. However, it is still challenging to register RGB-D images from a hand-held camera over a long video sequence into a globally consistent 3D model. Current methods often can lose tracking or drift and thus fail to reconstruct salient structures in large environments (e.g., parallel walls in different rooms). To address this problem, we propose a "fine-to-coarse" global registration algorithm that leverages robust registrations at finer scales to seed detection and enforcement of new correspondence and structural constraints at coarser scales. To test global registration algorithms, we provide a benchmark with 10,401 manually-clicked point correspondences in 25 scenes from the SUN3D dataset. During experiments with this benchmark, we find that our fine-to-coarse algorithm registers long RGB-D sequences better than previous methods

Writers' rooms: theories of contemporary authorship in portraits of creative spaces

This article analyzes two series of photographs and essays on writers’ rooms published in England and Canada in 2007 and 2008. The Guardian’s Writers Rooms series, with photographs by Eamon McCabe, ran in 2007. In the summer of 2008, The Vancouver International Writers and Readers Festival began to post its own version of The Guardian column on its website by displaying, each week leading up to the Festival in September, a different writer’s “writing space” and an accompanying paragraph. I argue that these images of writers’ rooms, which suggest a cultural fascination with authors’ private compositional practices and materials, reveal a great deal about theoretical constructions of authorship implicit in contemporary literary culture. Far from possessing the museum quality of dead authors’ spaces, rooms that are still being used, incorporating new forms of writing technology, and having drafts of manuscripts scattered around them, can offer insight into such well-worn and ineffable areas of speculation as inspiration, singular authorial genius, and literary productivity

The Gods die in museums

Recently, Johannes Neurath’s book, titled Subdue the gods, doubt the images (2020) was published, which, among other things, warns that, in the archaeological museums of Mexico, including the National Institute of Anthropology and History of Mexico City, there has been an “ontological mistreatment” of the sacred images of the pre-Hispanic era through their removal from their original locations and indistinct placement in large and cold rooms packed with monoliths, without any consideration for the fact that some were – and continue to be – images bestowed with power and influence by many communities today

Learning about Large Scale Image Search: Lessons from Global Scale Hotel Recognition to Fight Sex Trafficking

Hotel recognition is a sub-domain of scene recognition that involves determining what hotel is seen in a photograph taken in a hotel. The hotel recognition task is a challenging computer vision task due to the properties of hotel rooms, including low visual similarity between rooms in the same hotel and high visual similarity between rooms in different hotels, particularly those from the same chain. Building accurate approaches for hotel recognition is important to investigations of human trafficking. Images of human trafficking victims are often shared by traffickers among criminal networks and posted in online advertisements. These images are often taken in hotels. Using hotel recognition approaches to determine the hotel a victim was photographed in can assist in investigations and prosecutions of human traffickers. In this dissertation, I present an application for the ongoing capture of hotel imagery by the public, a large-scale curated dataset of hotel room imagery, deep learning approaches to hotel recognition based on this imagery, a visualization approach that provides insight into what networks trained on image similarity are learning, and an approach to image search focused on specific objects in scenes. Taken together, these contributions have resulted in a first in the world system that offers a solution to answering the question, `What hotel was this photograph taken in?\u27 at a global scale