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Singapore Management University

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Articles 661 - 690 of 959

Full-Text Articles in Graphics and Human Computer Interfaces

Empath-D: Empathetic Design For Accessibility, Kenny Tsu Wei Choo, Rajesh Krishna Balan, Kiat Wee Tan, Archan Misra, Youngki Lee Feb 2017

Empath-D: Empathetic Design For Accessibility, Kenny Tsu Wei Choo, Rajesh Krishna Balan, Kiat Wee Tan, Archan Misra, Youngki Lee

Research Collection School Of Computing and Information Systems

We describe our vision for Empath-D, our system to enable Empathetic User Interface Design. Our key idea is to leverage Virtual and Augmented Reality (VR / AR) displays to provide an Immersive Reality environment, where developers/designers can emulate impaired interactions by elderly or disabled users while testing the usability of their applications. Our early experiences with the Empath-D prototype show that Empath-D can emulate a cataract vision impairment of the elderly and guide designers to create accessible web pages with less mental workload.

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Unsupervised Visual Hashing With Semantic Assistant For Content-Based Image Retrieval, Lei Zhu, Jialie Shen, Liang Xie, Zhiyong Cheng Feb 2017

Unsupervised Visual Hashing With Semantic Assistant For Content-Based Image Retrieval, Lei Zhu, Jialie Shen, Liang Xie, Zhiyong Cheng

Research Collection School Of Computing and Information Systems

As an emerging technology to support scalable content-based image retrieval (CBIR), hashing has recently received great attention and became a very active research domain. In this study, we propose a novel unsupervised visual hashing approach called semantic-assisted visual hashing (SAVH). Distinguished from semi-supervised and supervised visual hashing, its core idea is to effectively extract the rich semantics latently embedded in auxiliary texts of images to boost the effectiveness of visual hashing without any explicit semantic labels. To achieve the target, a unified unsupervised framework is developed to learn hash codes by simultaneously preserving visual similarities of images, integrating the semantic …

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Active Video Summarization: Customized Summaries Via On-Line Interaction With The User, Ana Garcia Del Molino, Xavier Boix, Joo-Hwee Lim, Ah-Hwee Tan Feb 2017

Active Video Summarization: Customized Summaries Via On-Line Interaction With The User, Ana Garcia Del Molino, Xavier Boix, Joo-Hwee Lim, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

To facilitate the browsing of long videos, automatic video summarization provides an excerpt that represents its content. In the case of egocentric and consumer videos, due to their personal nature, adapting the summary to specific user’s preferences is desirable. Current approaches to customizable video summarization obtain the user’s preferences prior to the summarization process. As a result, the user needs to manually modify the summary to further meet the preferences. In this paper, we introduce Active Video Summarization (AVS), an interactive approach to gather the user’s preferences while creating the summary. AVS asks questions about the summary to update it …

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A Two-Sided Collaborative Transparent Display Supporting Workspace Awareness, Jiannan Li, Saul Greenberg, Ehud Sharlin Jan 2017

A Two-Sided Collaborative Transparent Display Supporting Workspace Awareness, Jiannan Li, Saul Greenberg, Ehud Sharlin

Research Collection School Of Computing and Information Systems

Transparent displays naturally support workspace awareness during face-to-face interactions. Viewers see another person’s actions through the display: gestures, gaze, body movements, and what one is manipulating on the display. Yet we can design even better collaborative transparent displays. First, collaborators on either side should be able to directly interact with workspace objects. Second, and more controversially, both sides should be capable of presenting different content. This affords: reversal of images/text in place (so that people on both sides see objects correctly); personal and private territories aligned atop each other; and GUI objects that provide different visuals for feedthrough vs. feedback. …

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Cross-Modal Recipe Retrieval: How To Cook This Dish?, Jingjing Chen, Lei Pang, Chong-Wah Ngo Jan 2017

Cross-Modal Recipe Retrieval: How To Cook This Dish?, Jingjing Chen, Lei Pang, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

In social media users like to share food pictures. One intelligent feature, potentially attractive to amateur chefs, is the recommendation of recipe along with food. Having this feature, unfortunately, is still technically challenging. First, the current technology in food recognition can only scale up to few hundreds of categories, which are yet to be practical for recognizing ten of thousands of food categories. Second, even one food category can have variants of recipes that differ in ingredient composition. Finding the best-match recipe requires knowledge of ingredients, which is a fine-grained recognition problem. In this paper, we consider the problem from …

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Easing Cross-Border Communication: Mobile-Mediated Communication And Its Framework, Kyungsub Choi, Young Soo Kim Jan 2017

Easing Cross-Border Communication: Mobile-Mediated Communication And Its Framework, Kyungsub Choi, Young Soo Kim

Research Collection School Of Computing and Information Systems

Communication is probably the most critical component of an organization engaged in a cross-border collaboration. Today’s smart devices substantially contribute to such communication. Combined with social media, mobile communication technologies are becoming the main platform for many core functions within organizations. In this paper, we identified seven media identifiable attributes: synchronicity (SYN), de-individuation and co-presence (DCP), accessibility readiness (ARD), cognizance of environment change (CEC), wearability-portability (WRB) modality-select (MDS) and visibility (VSB). These seven attributes significantly impact the course of mobile-mediated communication. We believe that development of a theoretical perspective that embraces the complexity of mobile-mediated communication is due in order …

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Cast2face: Assigning Character Names Onto Faces In Movie With Actor-Character Correspondence, Guangyu Gao, Mengdi Xu, Jialie Shen, Huangdong Ma, Shuicheng Yan Dec 2016

Cast2face: Assigning Character Names Onto Faces In Movie With Actor-Character Correspondence, Guangyu Gao, Mengdi Xu, Jialie Shen, Huangdong Ma, Shuicheng Yan

Research Collection School Of Computing and Information Systems

Automatically identifying characters in movies has attracted researchers' interest and led to several significant and interesting applications. However, due to the vast variation in character appearance as well as the weakness and ambiguity of available annotation, it is still a challenging problem. In this paper, we investigate this problem with the supervision of actor-character name correspondence provided by the movie cast. Our proposed framework, namely, Cast2Face, is featured by: 1) we restrict the assigned names within the set of character names in the cast; 2) for each character, by using the corresponding actor and movie name as keywords, we retrieve …

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Hashtag Recommendation With Topical Attention-Based Lstm, Yang Li, Ting Liu, Jing Jiang, Liang Zhang Dec 2016

Hashtag Recommendation With Topical Attention-Based Lstm, Yang Li, Ting Liu, Jing Jiang, Liang Zhang

Research Collection School Of Computing and Information Systems

Microblogging services allow users to create hashtags to categorize their posts. In recent years,the task of recommending hashtags for microblogs has been given increasing attention. However,most of existing methods depend on hand-crafted features. Motivated by the successful use oflong short-term memory (LSTM) for many natural language processing tasks, in this paper, weadopt LSTM to learn the representation of a microblog post. Observing that hashtags indicatethe primary topics of microblog posts, we propose a novel attention-based LSTM model whichincorporates topic modeling into the LSTM architecture through an attention mechanism. Weevaluate our model using a large real-world dataset. Experimental results show that …

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Hierarchical Visualization Of Video Search Results For Topic-Based Browsing, Yu-Gang Jiang, Jiajun Wang, Qiang Wang, Wei Liu, Chong-Wah Ngo Nov 2016

Hierarchical Visualization Of Video Search Results For Topic-Based Browsing, Yu-Gang Jiang, Jiajun Wang, Qiang Wang, Wei Liu, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

Existing video search engines return a ranked list of videos for each user query, which is not convenient for browsing the results of query topics that have multiple facets, such as the "early life," "personal life," and "presidency" of a query "Barack Obama." Organizing video search results into semantically structured hierarchies with nodes covering different topic facets can significantly improve the browsing efficiency for such queries. In this paper, we introduce a hierarchical visualization approach for video search result browsing, which can help users quickly understand the multiple facets of a query topic in a very well-organized manner. Given a …

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Reducing Adaptation Latency For Multi-Concept Visual Perception In Outdoor Environments, Maggie Wigness, John G. Rogers, Luis Ernesto Navarro-Serment, Arne Suppe, Bruce A. Draper Nov 2016

Reducing Adaptation Latency For Multi-Concept Visual Perception In Outdoor Environments, Maggie Wigness, John G. Rogers, Luis Ernesto Navarro-Serment, Arne Suppe, Bruce A. Draper

Research Collection School Of Computing and Information Systems

Multi-concept visual classification is emerging as a common environment perception technique, with applications in autonomous mobile robot navigation. Supervised visual classifiers are typically trained with large sets of images, hand annotated by humans with region boundary outlines followed by label assignment. This annotation is time consuming, and unfortunately, a change in environment requires new or additional labeling to adapt visual perception. The time is takes for a human to label new data is what we call adaptation latency. High adaptation latency is not simply undesirable but may be infeasible for scenarios with limited labeling time and resources. In this paper, …

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Vireo@Trecvid 2016: Multimedia Event Detection, Ad-Hoc Video Search, Video To Text Description, Hao Zhang, Lei Pang, Yi-Jie Lu, Chong-Wah Ngo Nov 2016

Vireo@Trecvid 2016: Multimedia Event Detection, Ad-Hoc Video Search, Video To Text Description, Hao Zhang, Lei Pang, Yi-Jie Lu, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

The vireo group participates in 3 tasks: multimedia event detection, ad-hoc video search, video-to-text description. In this paper, we will separately present frameworks for these tasks and discuss experimental results.

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Deep-Based Ingredient Recognition For Cooking Recipe Retrieval, Jingjing Chen, Chong-Wah Ngo Oct 2016

Deep-Based Ingredient Recognition For Cooking Recipe Retrieval, Jingjing Chen, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

Retrieving recipes corresponding to given dish pictures facilitates the estimation of nutrition facts, which is crucial to various health relevant applications. The current approaches mostly focus on recognition of food category based on global dish appearance without explicit analysis of ingredient composition. Such approaches are incapable for retrieval of recipes with unknown food categories, a problem referred to as zero-shot retrieval. On the other hand, content-based retrieval without knowledge of food categories is also difficult to attain satisfactory performance due to large visual variations in food appearance and ingredient composition. As the number of ingredients is far less than food …

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Fast Covariant Vlad For Image Search, Wan-Lei Zhao, Chong-Wah Ngo, Hanzi Wang Sep 2016

Fast Covariant Vlad For Image Search, Wan-Lei Zhao, Chong-Wah Ngo, Hanzi Wang

Research Collection School Of Computing and Information Systems

Vector of locally aggregated descriptor (VLAD) is a popular image encoding approach for its simplicity and better scalability over conventional bag-of-visual-word approach. In order to enhance its distinctiveness and geometric invariance, covariant VLAD (CVLAD) is proposed to pool local features based on their dominant orientations/characteristic scales, which leads to a geometric-aware representation. This representation achieves rotation/scale invariance when being associated with circular matching. However, the circular matching induces several times of computation overhead, which makes CVLAD hardly suitable for large-scale retrieval tasks. In this paper, the issue of computation overhead is alleviated by performing the circular matching in CVLAD's frequency …

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Automatic Hookworm Detection In Wireless Capsule Endoscopy Images, Xiao Wu, Honghan Chen, Tao Gan, Junzhou Chen, Chong-Wah Ngo, Qiang Peng Jul 2016

Automatic Hookworm Detection In Wireless Capsule Endoscopy Images, Xiao Wu, Honghan Chen, Tao Gan, Junzhou Chen, Chong-Wah Ngo, Qiang Peng

Research Collection School Of Computing and Information Systems

Wireless capsule endoscopy (WCE) has become a widely used diagnostic technique to examine inflammatory bowel diseases and disorders. As one of the most common human helminths, hookworm is a kind of small tubular structure with grayish white or pinkish semi-transparent body, which is with a number of 600 million people infection around the world. Automatic hookworm detection is a challenging task due to poor quality of images, presence of extraneous matters, complex structure of gastrointestinal, and diverse appearances in terms of color and texture. This is the first few works to comprehensively explore the automatic hookworm detection for WCE images. …

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Outlier-Robust Tensor Pca, Pan Zhou, Jiashi Feng Jul 2016

Outlier-Robust Tensor Pca, Pan Zhou, Jiashi Feng

Research Collection School Of Computing and Information Systems

Low-rank tensor analysis is important for various real applications in computer vision. However, existing methods focus on recovering a low-rank tensor contaminated by Gaussian or gross sparse noise and hence cannot effectively handle outliers that are common in practical tensor data. To solve this issue, we propose an outlier-robust tensor principle component analysis (OR-TPCA) method for simultaneous low-rank tensor recovery and outlier detection. For intrinsically low-rank tensor observations with arbitrary outlier corruption, OR-TPCA is the first method that has provable performance guarantee for exactly recovering the tensor subspace and detecting outliers under mild conditions. Since tensor data are naturally high-dimensional …

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Hci Testing In Laboratory Or Field Settings, Chuan-Hoo Tan, Austin Silva, Rich Lee, Kanliang Wang, Fiona Fui-Hoon Nah Jul 2016

Hci Testing In Laboratory Or Field Settings, Chuan-Hoo Tan, Austin Silva, Rich Lee, Kanliang Wang, Fiona Fui-Hoon Nah

Research Collection School Of Computing and Information Systems

This paper presents perspectives from both academia and practice on how an HCI testing is to be conducted and the deliberations that go into the testing. HCI testing can be conducted in closed-door laboratory or in a field setting. While there is an increased interest in field testing of an HCI artifact, there is always an enduring concern over how to administer a field testing given that the testers will have less control over the course of testing. In this paper, we cover HCI testing deliberation as well as the operational issues of field testing, and conclude the paper with …

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The Impact Of Security Cues On User Perceived Security In E-Commerce, Samuel N. Smith, Fiona Fui-Hoon Nah, Maggie X. Cheng Jul 2016

The Impact Of Security Cues On User Perceived Security In E-Commerce, Samuel N. Smith, Fiona Fui-Hoon Nah, Maggie X. Cheng

Research Collection School Of Computing and Information Systems

Users are expected to assess the level of security of e-commerce websites before conducting online transactions. In this research, we examine user assessment of security of e-commerce web pages based on cues presented on the web pages. A pilot study was conducted in which each subject assessed six e-commerce web pages with varying cues (i.e., HTTP vs. HTTPS, fraudulent vs. authentic URL, padlocks beside fields), and the findings are reported.

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Patient Engagement In The Medical Facility Waiting Room Using Gamified Healthcare Information Delivery, Raheel Hassan, Nathan W. Twyman, Fiona F. Nah, Keng Siau Jul 2016

Patient Engagement In The Medical Facility Waiting Room Using Gamified Healthcare Information Delivery, Raheel Hassan, Nathan W. Twyman, Fiona F. Nah, Keng Siau

Research Collection School Of Computing and Information Systems

This study explores the proposition that medical facility waiting rooms are an opportune setting to engage with and educate patients while they are waiting for care. In collaboration with emergency department (ED) personnel, we developed ER Hero, a tablet-based application for waiting rooms that introduces patients to ED professionals and operations through mini-games and story-like interaction. We evaluated this prototype with human participants to determine how well it performed when compared to paper-based information disclosure presenting the same information. Participants using the application exhibited increased ED knowledge, decreased nervousness, and increased interest. The gamified application outperformed a paper-based approach on …

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Cross-Modal Self-Taught Hashing For Large-Scale Image Retrieval, Liang Xie, Lei Zhu, Peng Pan, Yansheng Lu Jul 2016

Cross-Modal Self-Taught Hashing For Large-Scale Image Retrieval, Liang Xie, Lei Zhu, Peng Pan, Yansheng Lu

Research Collection School Of Computing and Information Systems

Cross-modal hashing integrates the advantages of traditional cross-modal retrieval and hashing, it can solve large-scale cross-modal retrieval effectively and efficiently. However, existing cross-modal hashing methods rely on either labeled training data, or lack semantic analysis. In this paper, we propose Cross-Modal Self-Taught Hashing (CMSTH) for large-scale cross-modal and unimodal image retrieval. CMSTH can effectively capture the semantic correlation from unlabeled training data. Its learning process contains three steps: first we propose Hierarchical Multi-Modal Topic Learning (HMMTL) to detect multi-modal topics with semantic information. Then we use Robust Matrix Factorization (RMF) to transfer the multi-modal topics to hash codes which are …

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Video Modeling And Learning On Riemannian Manifold For Emotion Recognition In The Wild, Mengyi Liu, Ruiping Wang, Shaoxin Li, Zhiwu Huang, Shiguang Shan, Xilin Chen Jun 2016

Video Modeling And Learning On Riemannian Manifold For Emotion Recognition In The Wild, Mengyi Liu, Ruiping Wang, Shaoxin Li, Zhiwu Huang, Shiguang Shan, Xilin Chen

Research Collection School Of Computing and Information Systems

In this paper, we present the method for our submission to the emotion recognition in the wild challenge (EmotiW). The challenge is to automatically classify the emotions acted by human subjects in video clips under real-world environment. In our method, each video clip can be represented by three types of image set models (i.e. linear subspace, covariance matrix, and Gaussian distribution) respectively, which can all be viewed as points residing on some Riemannian manifolds. Then different Riemannian kernels are employed on these set models correspondingly for similarity/ distance measurement. For classification, three types of classifiers, i.e. kernel SVM, logistic regression, …

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Smart Living For Elderly: Design And Human-Computer Interaction Considerations, Ranjana Sharma, Fiona Fui-Hoon Nah, Kavya Sharma, Teja S. Katta, Natalie Pang, Alvin Yong Jun 2016

Smart Living For Elderly: Design And Human-Computer Interaction Considerations, Ranjana Sharma, Fiona Fui-Hoon Nah, Kavya Sharma, Teja S. Katta, Natalie Pang, Alvin Yong

Research Collection School Of Computing and Information Systems

To address aging challenges, we examine the concept of smart living and its applications for the elderly. Smart living refers to improving quality of life by transforming environments to become more intelligent and adaptable to users. In this paper, we discuss how smart living applications can help to address the needs of the elderly, as well as the design and human-computer interaction considerations for such applications.

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Patient Engagement In The Medical Facility Waiting Room Using Gamified Healthcare Information Delivery, Raheel Hassan, Nathan W. Twyman, Fiona Fui-Hoon Nah, Keng Siau Jun 2016

Patient Engagement In The Medical Facility Waiting Room Using Gamified Healthcare Information Delivery, Raheel Hassan, Nathan W. Twyman, Fiona Fui-Hoon Nah, Keng Siau

Research Collection School Of Computing and Information Systems

This study explores the proposition that medical facility waiting rooms are an opportune setting to engage with and educate patients while they are waiting for care. In collaboration with emergency department (ED) personnel, we developed ER Hero, a tablet-based application for waiting rooms that introduces patients to ED professionals and operations through mini-games and story-like interaction. We evaluated this prototype with human participants to determine how well it performed when compared to paper-based information disclosure presenting the same information. Participants using the application exhibited increased ED knowledge, decreased nervousness, and increased interest. The gamified application outperformed a paper-based approach on …

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Exemplar-Driven Top-Down Saliency Detection Via Deep Association, Shengfeng He, Rynson W. H. Lau, Qingxiong Yang Jun 2016

Exemplar-Driven Top-Down Saliency Detection Via Deep Association, Shengfeng He, Rynson W. H. Lau, Qingxiong Yang

Research Collection School Of Computing and Information Systems

Top-down saliency detection is a knowledge-driven search task. While some previous methods aim to learn this "knowledge" from category-specific data, others transfer existing annotations in a large dataset through appearance matching. In contrast, we propose in this paper a locateby-exemplar strategy. This approach is challenging, as we only use a few exemplars (up to 4) and the appearances among the query object and the exemplars can be very different. To address it, we design a two-stage deep model to learn the intra-class association between the exemplars and query objects. The first stage is for learning object-to-object association, and the second …

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Hci Testing In Laboratory Or Field Settings, Chuan-Hoo Tan, Austin Silva, Rich Lee, Kanliang Wang, Fiona Fui-Hoon Nah Jun 2016

Hci Testing In Laboratory Or Field Settings, Chuan-Hoo Tan, Austin Silva, Rich Lee, Kanliang Wang, Fiona Fui-Hoon Nah

Research Collection School Of Computing and Information Systems

This paper presents perspectives from both academia and practice on how an HCI testing is to be conducted and the deliberations that go into the testing. HCI testing can be conducted in closed-door laboratory or in a field setting. While there is an increased interest in field testing of an HCI artifact, there is always an enduring concern over how to administer a field testing given that the testers will have less control over the course of testing. In this paper, we cover HCI testing deliberation as well as the operational issues of field testing, and conclude the paper with …

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Serendipity-Driven Celebrity Video Hyperlinking, Shujun Yang, Lei Pang, Chong-Wah Ngo, Benoit Huet Jun 2016

Serendipity-Driven Celebrity Video Hyperlinking, Shujun Yang, Lei Pang, Chong-Wah Ngo, Benoit Huet

Research Collection School Of Computing and Information Systems

This demo showcases the utility of video hyperlinks with celebrities as the link anchors and their social circles as targets, aiming to help users quickly explore the aboutness of a celebrity by link traversal. Through content analysis, our system embeds hyperlinks into videos such that users can click-and-jump between celebrity faces in different videos to get-to-know their social circles. One peculiar feature is the ability of the system in providing links that maximize users' chance encounter, or serendipitous experience, beyond information need. Our system is enabled by two key components, name-face association and diversity-based ranking, for the aboutness and serendipity …

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Event Detection With Zero Example: Select The Right And Suppress The Wrong Concepts, Yi-Jie Lu, Hao Zhang, Maaike De Boer, Chong-Wah Ngo Jun 2016

Event Detection With Zero Example: Select The Right And Suppress The Wrong Concepts, Yi-Jie Lu, Hao Zhang, Maaike De Boer, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

Complex video event detection without visual examples is a very challenging issue in multimedia retrieval. We present a state-of-the-art framework for event search without any need of exemplar videos and textual metadata in search corpus. To perform event search given only query words, the core of our framework is a large, pre-built bank of concept detectors which can understand the content of a video in the perspective of object, scene, action and activity concepts. Leveraging such knowledge can effectively narrow the semantic gap between textual query and the visual content of videos. Besides the large concept bank, this paper focuses …

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An Autonomous Agent For Learning Spatiotemporal Models Of Human Daily Activities, Shan Gao, Ah-Hwee Tan May 2016

An Autonomous Agent For Learning Spatiotemporal Models Of Human Daily Activities, Shan Gao, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

Activities of Daily Living (ADLs) refer to activities performed by individuals on a daily basis. As ADLs are indicatives of a person’s habits, lifestyle, and well being, learning the knowledge of people’s ADL routine has great values in the healthcare and consumer domains. In this paper, we propose an autonomous agent, named Agent for Spatia-Temporal Activity Pattern Modeling (ASTAPM), being able to learn spatial and temporal patterns of human ADLs. ASTAPM utilises a self-organizing neural network model named Spatiotemporal - Adaptive Resonance Theory (ST-ART). ST-ART is capable of integrating multimodal contextual information, involving the time and space, wherein the ADL …

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Modeling Human-Like Non-Rationality For Social Agents, Jaroslaw Kochanowicz, Ah-Hwee Tan, Daniel Thalmann May 2016

Modeling Human-Like Non-Rationality For Social Agents, Jaroslaw Kochanowicz, Ah-Hwee Tan, Daniel Thalmann

Research Collection School Of Computing and Information Systems

Humans are not rational beings. Deviations from rationality in human thinking are currently well documented [25] as non-reducible to rational pursuit of egoistic benefit or its occasional distortion with temporary emotional excitation, as it is often assumed. This occurs not only outside conceptual reasoning or rational goal realization but also subconsciously and often in certainty that they did not and could not take place ‘in my case’. Non-rationality can no longer be perceived as a rare affective abnormality in otherwise rational thinking, but as a systemic, permanent quality, ’a design feature’ of human cognition. While social psychology has systematically addressed …

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Efficient 3d Dental Identification Via Signed Feature Histogram And Learning Keypoint Detection, Zhiyuan Zhang, Sim Heng Ong, Xin Zhong, Kelvin W. C. Foong May 2016

Efficient 3d Dental Identification Via Signed Feature Histogram And Learning Keypoint Detection, Zhiyuan Zhang, Sim Heng Ong, Xin Zhong, Kelvin W. C. Foong

Research Collection School Of Computing and Information Systems

Current methods of dental identification are mainly based on 2D dental radiographs which suffer from speed and accuracy limitations. In this paper, we present an efficient dental identification approach based on 3D dental models. We propose a novel shape descriptor, the Signed Feature Histogram (SFH), which is highly discriminative and can be easily computed to describe the local surface. Based on the SFH, a learning keypoint detection method is adopted to accurately detect the desired keypoints on both antemortem (AM) and postmortem (PM) models. For a given PM model, the optimal initial alignment to the AM model to be matched …

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You Are Being Watched: Bystanders' Perspective On The Use Of Camera Devices In Public Spaces, Samarth Singhal, Carman Neustaedter, Thecla Schiphorst, Anthony Tang, Abhisekh Patra, Rui Pan May 2016

You Are Being Watched: Bystanders' Perspective On The Use Of Camera Devices In Public Spaces, Samarth Singhal, Carman Neustaedter, Thecla Schiphorst, Anthony Tang, Abhisekh Patra, Rui Pan

Research Collection School Of Computing and Information Systems

We are observing an increase in the use of smartphones and wearable devices in public places for streaming and recording video. Yet the use of cameras in these devices can infringe upon the privacy of the people in the surrounding environment by inadvertently capturing them. This paper presents findings from an in-situ exploratory study that investigates bystanders' reactions and feelings towards streaming and recording videos with smartphones and wearable glasses in public spaces. We use the interview results to guide an exploration of design directions for mobile video.

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