Publications

By Francine Chen (Clear Search)

2014
Publication Details
  • ICWSM (The 8th International AAAI Conference on Weblogs and Social Media)
  • Jun 1, 2014

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A topic-independent sentiment model is commonly used to estimate sentiment in microblogs. But for movie and product reviews, domain adaptation has been shown to improve sentiment estimation performance. We investigated the utility of topic-dependent polarity estimation models for microblogs. We examined both a model trained on Twitter tweets containing a target keyword and a model trained on an enlarged set of tweets containing terms related to a topic. Comparing the performance of the topic-dependent models to a topic-independent model trained on a general sample of tweets, we noted that for some topics, topic-dependent models performed better. We then propose a method for predicting which topics are likely to have better sentiment estimation performance when a topic-dependent sentiment model is used.
Publication Details
  • ACM ICMR 2014
  • Apr 1, 2014

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Motivated by scalable partial-duplicate visual search, there has been growing interest on a wealth of compact and efficient binary feature descriptors (e.g. ORB, FREAK, BRISK). Typically, binary descriptors are clustered into codewords and quantized with Hamming distance, which follows conventional bag-of-words strategy. However, such codewords formulated in Hamming space did not present obvious indexing and search performance improvement as compared to the Euclidean ones. In this paper, without explicit codeword construction, we explore to utilize binary descriptors as direct codebook indices (addresses). We propose a novel approach to build multiple index tables which parallelly check the collision of same hash values. The evaluation is performed on two public image datasets: DupImage and Holidays. The experimental results demonstrate the index efficiency and retrieval accuracy of our approach.
2013
Publication Details
  • IUI 2013
  • Mar 19, 2013

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People frequently capture photos with their smartphones, and some are starting to capture images of documents. However, the quality of captured document images is often lower than expected, even when applications that perform post-processing to improve the image are used. To improve the quality of captured images before post-processing, we developed a Smart Document Capture (SmartDCap) application that provides real-time feedback to users about the likely quality of a captured image. The quality measures capture the sharpness and framing of a page or regions on a page, such as a set of one or more columns, a part of a column, a figure, or a table. Using our approach, while users adjust the camera position, the application automatically determines when to take a picture of a document to produce a good quality result. We performed a subjective evaluation comparing SmartDCap and the Android Ice Cream Sandwich (ICS) camera application; we also used raters to evaluate the quality of the captured images. Our results indicate that users find SmartDCap to be as easy to use as the standard ICS camera application. Additionally, images captured using SmartDCap are sharper and better framed on average than images using the ICS camera application.
2012
Publication Details
  • ICPR 2012
  • Nov 11, 2012

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Images of document pages have different characteristics than images of natural scenes, and so the sharpness measures developed for natural scene images do not necessarily extend to document images primarily composed of text. We present an efficient and simple method for effectively estimating the sharpness/ blurriness of document images that also performs well on natural scenes. Our method can be used to predict the sharpness in scenarios where images are blurred due to camera-motion (or hand-shake), defocus, or inherent properties of the imaging system. The proposed method outperforms the perceptually-based, no-reference sharpness work of [1] and [4], which was shown to perform better than 14 other no-reference sharpness measures on the LIVE dataset.
Publication Details
  • International Journal on Document Analysis and Recognition (IJDAR): Volume 15, Issue 3 (2012), pp. 167-182.
  • Sep 1, 2012

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When searching or browsing documents, the genre of a document is an important consideration that complements topical characterization. We examine design considerations for automatic tagging of office document pages with genre membership. These include selecting features that characterize genre-related information in office documents, examining the utility of text-based features and image-based features, and proposing a simple ensemble method to improve genre identification performance. In the open-set identification of four office document genres, our experiments show that when combined with image-based features, text-based features do not significantly influence performance. These results provide support for a topic-independent approach to genre identification of office documents. Experiments also show that our simple ensemble method significantly improves performance relative to using a support vector machine (SVM) classifier alone. We demonstrate the utility of our approach by integrating our automatic genre tags in a faceted search and browsing application for office document collections.
2011
Publication Details
  • CHI 2011
  • May 7, 2011

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For document visualization, folding techniques provide a focus-plus-context approach with fairly high legibility on flat sections. To enable richer interaction, we explore the design space of multi-touch document folding. We discuss several design considerations for simple modeless gesturing and compatibility with standard Drag and Pinch gestures, and categorize gesture models along the characteristics of Symmetric/Asymmetric and Sequential/Parallel, which yields three gesture models. We built a prototype document workspace application that integrates folding and standard gestures, and a prototype for experimenting with the gesture models. A user study was conducted to compare the three models and to analyze the factors of fold direction, target symmetry, and target tolerance in user performance of folding a document to a specific shape. Our results indicate that all three factors were significant for task times, and parallelism was greater for symmetric targets.

DiG: A task-based approach to product search

Publication Details
  • IUI 2011
  • Feb 13, 2011

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While there are many commercial systems designed to help people browse and compare products, these interfaces are typically product centric. To help users more efficiently identify products that match their needs, we instead focus on building a task centric interface and system. With this approach, users initially answer questions about the types of situations in which they expect to use the product. The interface reveals the types of products that match their needs and exposes high-level product features related to the kinds of tasks in which they have expressed an interest. As users explore the interface, they can reveal how those high-level features are linked to actual product data, including customer reviews and product specifications. We developed semi-automatic methods to extract the high-level features used by the system from online product data. These methods identify and group product features, mine and summarize opinions about those features, and identify product uses. User studies verified our focus on high-level features for browsing and low-level features and specifications for comparison.  
2010
Publication Details
  • ACM Multimedia
  • Oct 25, 2010

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FACT is an interactive paper system for fine-grained interaction with documents across the boundary between paper and computers. It consists of a small camera-projector unit, a laptop, and ordinary paper documents. With the camera-projector unit pointing to a paper document, the system allows a user to issue pen gestures on the paper document for selecting fine-grained content and applying various digital functions. For example, the user can choose individual words, symbols, figures, and arbitrary regions for keyword search, copy and paste, web search, and remote sharing. FACT thus enables a computer-like user experience on paper. This paper interaction can be integrated with laptop interaction for cross-media manipulations on multiple documents and views. We present the infrastructure, supporting techniques and interaction design, and demonstrate the feasibility via a quantitative experiment. We also propose applications such as document manipulation, map navigation and remote collaboration.
Publication Details
  • ACM DocEng 2010
  • Sep 21, 2010

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We present a method for picture detection in document page images, which can come from scanned or camera images, or rendered from electronic file formats. Our method uses OCR to separate out the text and applies the Normalized Cuts algorithm to cluster the non-text pixels into picture regions. A refinement step uses the captions found in the OCR text to deduce how many pictures are in a picture region, thereby correcting for under- and over-segmentation. A performance evaluation scheme is applied which takes into account the detection quality and fragmentation quality. We benchmark our method against the ABBYY application on page images from conference papers.

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Browsing and searching for documents in large, online enterprise document repositories are common activities. While internet search produces satisfying results for most user queries, enterprise search has not been as successful because of differences in document types and user requirements. To support users in finding the information they need in their online enterprise repository, we created DocuBrowse, a faceted document browsing and search system. Search results are presented within the user-created document hierarchy, showing only directories and documents matching selected facets and containing text query terms. In addition to file properties such as date and file size, automatically detected document types, or genres, serve as one of the search facets. Highlighting draws the user’s attention to the most promising directories and documents while thumbnail images and automatically identified keyphrases help select appropriate documents. DocuBrowse utilizes document similarities, browsing histories, and recommender system techniques to suggest additional promising documents for the current facet and content filters.
Publication Details
  • Fuji Xerox Technical Report No. 19, pp. 88-100
  • Jan 1, 2010

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Browsing and searching for documents in large, online enterprise document repositories is an increasingly common problem. While users are familiar and usually satisfied with Internet search results for information, enterprise search has not been as successful because of differences in data types and user requirements. To support users in finding the information they need from electronic and scanned documents in their online enterprise repository, we created an automatic detector for genres such as papers, slides, tables, and photos. Several of those genres correspond roughly to file name extensions but are identified automatically using features of the document. This genre identifier plays an important role in our faceted document browsing and search system. The system presents documents in a hierarchy as typically found in enterprise document collections. Documents and directories are filtered to show only documents matching selected facets and containing optional query terms and to highlight promising directories. Thumbnail images and automatically identified keyphrases help select desired documents.
2008
Publication Details
  • ACM Multimedia 2008
  • Oct 27, 2008

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Audio monitoring has many applications but also raises pri- vacy concerns. In an attempt to help alleviate these con- cerns, we have developed a method for reducing the intelli- gibility of speech while preserving intonation and the ability to recognize most environmental sounds. The method is based on identifying vocalic regions and replacing the vocal tract transfer function of these regions with the transfer function from prerecorded vowels, where the identity of the replacement vowel is independent of the identity of the spoken syllable. The audio signal is then re-synthesized using the original pitch and energy, but with the modi ed vocal tract transfer function. We performed an intelligibility study which showed that environmental sounds remained recognizable but speech intelligibility can be dramatically reduced to a 7% word recognition rate.
Publication Details
  • ACM Multimedia 2008 Workshop: TrecVid Summarization 2008 (TVS'08)
  • Oct 26, 2008

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In this paper we describe methods for video summarization in the context of the TRECVID 2008 BBC Rushes Summarization task. Color, motion, and audio features are used to segment, filter, and cluster the video. We experiment with varying the segment similarity measure to improve the joint clustering of segments with and without camera motion. Compared to our previous effort for TRECVID 2007 we have reduced the complexity of the summarization process as well as the visual complexity of the summaries themselves. We find our objective (inclusion) performance to be competitive with systems exhibiting similar subjective performance.
Publication Details
  • IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2008
  • Jun 24, 2008

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Current approaches to pose estimation and tracking can be classified into two categories: generative and discriminative. While generative approaches can accurately determine human pose from image observations, they are computationally intractable due to search in the high dimensional human pose space. On the other hand, discriminative approaches do not generalize well, but are computationally efficient. We present a hybrid model that combines the strengths of the two in an integrated learning and inference framework. We extend the Gaussian process latent variable model (GPLVM) to include an embedding from observation space (the space of image features) to the latent space. GPLVM is a generative model, but the inclusion of this mapping provides a discriminative component, making the model observation driven. Observation Driven GPLVM (OD-GPLVM) not only provides a faster inference approach, but also more accurate estimates (compared to GPLVM) in cases where dynamics are not sufficient for the initialization of search in the latent space. We also extend OD-GPLVM to learn and estimate poses from parameterized actions/gestures. Parameterized gestures are actions which exhibit large systematic variation in joint angle space for different instances due to difference in contextual variables. For example, the joint angles in a forehand tennis shot are function of the height of the ball (Figure 2). We learn these systematic variations as a function of the contextual variables. We then present an approach to use information from scene/object to provide context for human pose estimation for such parameterized actions.

FXPAL Interactive Search Experiments for TRECVID 2007

Publication Details
  • TRECVid 2007
  • Mar 1, 2008

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In 2007 FXPAL submitted results for two tasks: rushes summarization and interactive search. The rushes summarization task has been described at the ACM Multimedia workshop. Interested readers are referred to that publication for details. We describe our interactive search experiments in this notebook paper.
2007

DOTS: Support for Effective Video Surveillance

Publication Details
  • Fuji Xerox Technical Report No. 17, pp. 83-100
  • Nov 1, 2007

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DOTS (Dynamic Object Tracking System) is an indoor, real-time, multi-camera surveillance system, deployed in a real office setting. DOTS combines video analysis and user interface components to enable security personnel to effectively monitor views of interest and to perform tasks such as tracking a person. The video analysis component performs feature-level foreground segmentation with reliable results even under complex conditions. It incorporates an efficient greedy-search approach for tracking multiple people through occlusion and combines results from individual cameras into multi-camera trajectories. The user interface draws the users' attention to important events that are indexed for easy reference. Different views within the user interface provide spatial information for easier navigation. DOTS, with over twenty video cameras installed in hallways and other public spaces in our office building, has been in constant use for a year. Our experiences led to many changes that improved performance in all system components.
Publication Details
  • TRECVID Video Summarization Workshop at ACM Multimedia 2007
  • Sep 28, 2007

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This paper describes a system for selecting excerpts from unedited video and presenting the excerpts in a short sum- mary video for eciently understanding the video contents. Color and motion features are used to divide the video into segments where the color distribution and camera motion are similar. Segments with and without camera motion are clustered separately to identify redundant video. Audio fea- tures are used to identify clapboard appearances for exclu- sion. Representative segments from each cluster are selected for presentation. To increase the original material contained within the summary and reduce the time required to view the summary, selected segments are played back at a higher rate based on the amount of detected camera motion in the segment. Pitch-preserving audio processing is used to bet- ter capture the sense of the original audio. Metadata about each segment is overlayed on the summary to help the viewer understand the context of the summary segments in the orig- inal video.

DOTS: Support for Effective Video Surveillance

Publication Details
  • ACM Multimedia 2007, pp. 423-432
  • Sep 24, 2007

Abstract

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DOTS (Dynamic Object Tracking System) is an indoor, real-time, multi-camera surveillance system, deployed in a real office setting. DOTS combines video analysis and user interface components to enable security personnel to effectively monitor views of interest and to perform tasks such as tracking a person. The video analysis component performs feature-level foreground segmentation with reliable results even under complex conditions. It incorporates an efficient greedy-search approach for tracking multiple people through occlusion and combines results from individual cameras into multi-camera trajectories. The user interface draws the users' attention to important events that are indexed for easy reference. Different views within the user interface provide spatial information for easier navigation. DOTS, with over twenty video cameras installed in hallways and other public spaces in our office building, has been in constant use for a year. Our experiences led to many changes that improved performance in all system components.

FXPAL MediaMagic Video Search System

Publication Details
  • ACM Conf. on Image and Video Retrieval 2007
  • Jul 29, 2007

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This paper describes FXPAL's interactive video search application, "MediaMagic". FXPAL has participated in the TRECVID interactive search task since 2004. In our search application we employ a rich set of redundant visual cues to help the searcher quickly sift through the video collection. A central element of the interface and underlying search engine is a segmentation of the video into stories, which allows the user to quickly navigate and evaluate the relevance of moderately-sized, semantically-related chunks.
Publication Details
  • ICME 2007, pp. 675-678
  • Jul 2, 2007

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In this paper we describe the analysis component of an indoor, real-time, multi-camera surveillance system. The analysis includes: (1) a novel feature-level foreground segmentation method which achieves efficient and reliable segmentation results even under complex conditions, (2) an efficient greedy search based approach for tracking multiple people through occlusion, and (3) a method for multi-camera handoff that associates individual trajectories in adjacent cameras. The analysis is used for an 18 camera surveillance system that has been running continuously in an indoor business over the past several months. Our experiments demonstrate that the processing method for people detection and tracking across multiple cameras is fast and robust.
2006
Publication Details
  • EACL (11th Conference of the European Chapter of the Association for Computational Linguistics)
  • Apr 3, 2006

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Probabilistic Latent Semantic Analysis (PLSA) models have been shown to provide a better model for capturing polysemy and synonymy than Latent Semantic Analysis (LSA). However, the parameters of a PLSA model are trained using the Expectation Maximization (EM) algorithm, and as a result, the trained model is dependent on the initialization values so that performance can be highly variable. In this paper we present a method for using LSA analysis to initialize a PLSA model. We also investigated the performance of our method for the tasks of text segmentation and retrieval on personal-size corpora, and present results demonstrating the efficacy of our proposed approach.
1997

Metadata for Mixed Media Access.

Publication Details
  • In Managing Multimedia Data: Using Metadata to Integrate and Apply Digital Data. A. Sheth and W. Klas (eds.), McGraw Hill, 1997.
  • Feb 1, 1997

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In this chapter, we discuss mixed-media access, an information access paradigm for multimedia data in which the media type of a query may differ from that of the data. This allows a single query to be used to retrieve information from data consisting of multiple types of media. In addition, multiple queries formulated in different media types can be used to more accurately specify the data to be retrieved. The types of media considered in this paper are speech, images of text, and full-length text. Some examples of metadata for mixed-media access are locations of keywords in speech and images, identification of speakers, locations of emphasized regions in speech, and locations of topic boundaries in text. Algorithms for automatically generating this metadata are described, including word spotting, speaker segmentation, emphatic speech detection, and subtopic boundary location. We illustrate the use of mixed-media access with an example of information access from multimedia data surrounding a formal presentation.