Anticipating Visual Representations from Unlabeled Video

Anticipating actions and objects before they start or appear is a difficult problem in computer vision with several real-world applications. This task is challenging partly because it requires leveraging extensive knowledge of the world that is difficult to write down. We believe that a promising resource for efficiently learning this knowledge is through readily available unlabeled video. We present a framework that capitalizes on temporal structure in unlabeled video to learn to anticipate human actions and objects. The key idea behind our approach is that we can train deep networks to predict the visual representation of images in the future. Visual representations are a promising prediction target because they encode images at a higher semantic level than pixels yet are automatic to compute. We then apply recognition algorithms on our predicted representation to anticipate objects and actions. We experimentally validate this idea on two datasets, anticipating actions one second in the future and objects five seconds in the future.Comment: CVPR 201

Analysis of EZproxy server logs to visualise research activity in Curtin’s online library

© 2019, Emerald Publishing Limited. Purpose: The purpose of this paper is to develop data visualisation proof of concept prototypes that will enable the Curtin University Library team to explore its users’ information-seeking behaviour and collection use online by analysing the library’s EZproxy logs. Design/methodology/approach: Curtin Library’s EZproxy log file data from 2013 to 2017 is used to develop the data visualisation prototypes using Unity3D software. Findings: Two visualisation prototypes from the EZproxy data set are developed. The first, “Global Visualisation of Curtin Research Activity”, uses a geographical map of the world as a platform to show where each research request comes from, the time each is made and the file size of the request. The second prototype, “Database Usage Visualisation”, shows the use of the library’s various subscription databases by staff and students daily, over a month in April 2017. Research limitations/implications: The paper has following limitations: working to a tight timeline of ten weeks; time taken to cleanse noise data; and requirements for storing and hosting the voluminous data sets. Practical implications: The prototypes provide visual evidence of the use of Curtin Library’s digital resources at any time and from anywhere by its users, demonstrating the demand for the library’s online service offerings. These prototype evidence-based data visualisations empower the library to communicate in a compelling and interesting way how its services and subscriptions support Curtin University’s missions. Originality/value: The paper provides innovative approaches to create immersive 3D data visualisation prototypes to make sense of complex EZproxy data sets

Subject Searching in Online Catalogs: Metaknowledge Used by Experienced Searchers

This paper begins to identify and characterize the knowledge used by experienced librarians while searching for subject information in online catalogs. Ten experienced librarians performed the same set of six subject searches in an online catalog. Investigated was the knowledge used to solve retrieval problems. This knowledge represents expertise in the use of the catalog. Data were collected through the use of think-aloud protocols, transaction logs, and structured interviews. Knowledge was defined as knowledge of objects (factual knowledge), knowledge of events (experiential knowledge), knowledge of performance (process knowledge), and metaknowledge. Metaknowledge is the sense of whole derived from the integration of factual, process, and experiential knowledge about the search and the conditions under which it is performed. The focus of this paper is on metaknowledge. For evidence of metaknowledge the data were examined for explanations that participants gave for their actions and observations, and for ways that participants evaluated their own progress during the process of searching. Reasons and explanations given by searchers were related to all phases of the library information retrieval process from the user's receipt of material to policies for collection development, and not just events directly related to the performance of a particular search task

Recent Developments in Data Warehousing

Data warehousing is a strategic business and IT initiative in many organizations today. Data warehouses can be developed in two alternative ways -- the data mart and the enterprise-wide data warehouse strategies -- and each has advantages and disadvantages. To create a data warehouse, data must be extracted from source systems, transformed, and loaded to an appropriate data store. Depending on the business requirements, either relational or multidimensional database technology can be used for the data stores. To provide a multidimensional view of the data using a relational database, a star schema data model is used. Online analytical processing can be performed on both kinds of database technology. Metadata about the data in the warehouse is important for IT and end users. A variety of data access tools and applications can be used with a data warehouse - SQL queries, management reporting systems, managed query environments, DSS/EIS, enterprise intelligence portals, data mining, and customer relationship management. A data warehouse can be used to support a variety of users - executive, managers, analysts, operational personnel, customers, and suppliers. Data warehousing concepts are brought to life through a case study of Harrah\u27s Entertainment, a firm that became a leader in the gaming industry with its CRM business strategy supported by data warehousing

Model Behavior: Using Photogrammetry for Collections Storage Planning

Proper and efficient collections storage is often a challenge for museums. As collections outgrow their facilities, institutions struggle to find additional space, often resorting to hasty moves of their objects into ill-fitting placements. A large-scale collections move is a slowgoing process, requiring manual measurement and countless trial-and-error sessions. An unnoticed support beam, a low entryway, or uneven flooring can derail even the most well-planned collections move, costing an organization unexpected additions in time and labor expenses. Advancements in emerging technologies, however, may soon eliminate this problem. This capstone explores the use of photogrammetry and 3D modeling to plan a collections storage move in a virtual environment. It examines the relationship between museums and technology through an analysis of museum studies literature, and showcases examples from the archaeology, architecture, and design fields to demonstrate the potential of photogrammetry. A collections move project using this technology for the digital modeling of storage spaces is proposed and detailed. Through the proposed project, I argue that the use of these technologies to design collections storage will greatly optimize a collections move

Volume 6, Number 2, June 1986 OLAC Newsletter

Digitized June 1986 issue of the OLAC Newsletter

Automatic Extraction of Attributes from Printed Indian Cheque Images by Template Matching Technique

Reserve Bank of India (RBI) has introduced Cheque Truncation System (CTS) for Indian banks in order to reduce the time required for physical movement of cheques between the clearance departments. However, other processes including database entry and verification are carried out manually. The proposal here is to eliminate the manual intervention by extracting the attributes from the input cheque image and updating the database automatically which significantly would reduce the time lapse on filling up the data into the database. Automatic database updating also contributes to provide secure data retrieval through querying system for verification of attributes by concerned banks. In this paper, a novel approach to extract printed attributes from Indian Bank cheque images based on their template structures is proposed. Template structures are determined by extracting the MICR code from the input cheque image. Important attributes region is segmented, and the printed data is recognized. Extensive experiments demonstrate the efficacy of the proposed method