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Physical Sciences and Mathematics Commons™
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Graphics and Human Computer Interfaces
Singapore Management University
Research Collection School Of Computing and Information Systems
- Keyword
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- Augmented reality (2)
- Recipe retrieval (2)
- Remote collaboration (2)
- VR (2)
- AR (1)
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- Animated transitions (1)
- Collaborative physical tasks (1)
- Color sketch query (1)
- Command and value selection (1)
- Concept combination (1)
- Concept query (1)
- Concept selection (1)
- Concept-based modeling (1)
- Contextual advertising (1)
- Covariance matrices (1)
- Cross-modal learning (1)
- Cross-modal retrieval (1)
- Cscw (1)
- Dietary app (1)
- Discriminative SPD matrices;Riemannian geometry;SPD manifold;geometry-aware SPD similarity learning;PSD manifold (1)
- Entertainment (1)
- Event Segmentation (1)
- Face recognition (1)
- Food image recognition (1)
- GANs; Progressive growing; Wasserstein divergence; Wasserstein metric (1)
- Game design (1)
- Geocaching (1)
- Gesture Recognition (1)
- Gesture elicitation (1)
- Gestures (1)
Articles 1 - 28 of 28
Full-Text Articles in Physical Sciences and Mathematics
The Living Wall Display: Physical Augmentation Of Interactive Content Using An Autonomous Mobile Display, Yuki Onishi, Yoshiki Kudo, Kazuki Takashima, Anthony Tang, Yoshifumi Kitamura
The Living Wall Display: Physical Augmentation Of Interactive Content Using An Autonomous Mobile Display, Yuki Onishi, Yoshiki Kudo, Kazuki Takashima, Anthony Tang, Yoshifumi Kitamura
Research Collection School Of Computing and Information Systems
The Living Wall Display displays interactive content on a mobile wall screen that moves in concert with content animation. To augment the interaction experience, the display dynamically changes its position and orientation, responding to the content animation triggered by user interactions. We implement three proof of concept prototypes that represent pseudo force impact of the interactive content using physical screen movement. Pilot studies show that the Living Wall augments content expressiveness, and increases the sense of presence of the screen content.
Cross Euclidean-To-Riemannian Metric Learning With Application To Face Recognition From Video, Zhiwu Huang, R. Wang, S. Shan, Gool L Van
Cross Euclidean-To-Riemannian Metric Learning With Application To Face Recognition From Video, Zhiwu Huang, R. Wang, S. Shan, Gool L Van
Research Collection School Of Computing and Information Systems
Riemannian manifolds have been widely employed for video representations in visual classification tasks including video-based face recognition. The success mainly derives from learning a discriminant Riemannian metric which encodes the non-linear geometry of the underlying Riemannian manifolds. In this paper, we propose a novel metric learning framework to learn a distance metric across a Euclidean space and a Riemannian manifold to fuse average appearance and pattern variation of faces within one video. The proposed metric learning framework can handle three typical tasks of video-based face recognition: Video-to-Still, Still-to-Video and Video-to-Video settings. To accomplish this new framework, by exploiting typical Riemannian …
Active Matting, Xin Yang, Ke Xu, Shaozhe Chen, Shengfeng He, Baocai Yin, Rynson Lau
Active Matting, Xin Yang, Ke Xu, Shaozhe Chen, Shengfeng He, Baocai Yin, Rynson Lau
Research Collection School Of Computing and Information Systems
Image matting is an ill-posed problem. It requires a user input trimap or some strokes to obtain an alpha matte of the foreground object. A fine user input is essential to obtain a good result, which is either time consuming or suitable for experienced users who know where to place the strokes. In this paper, we explore the intrinsic relationship between the user input and the matting algorithm to address the problem of where and when the user should provide the input. Our aim is to discover the most informative sequence of regions for user input in order to produce …
Vr Safari Park: A Concept-Based World Building Interface Using Blocks And World Tree, Shotaro Ichikawa, Anthony Tang, Kazuki Takashima, Yoshifumi Kitamura
Vr Safari Park: A Concept-Based World Building Interface Using Blocks And World Tree, Shotaro Ichikawa, Anthony Tang, Kazuki Takashima, Yoshifumi Kitamura
Research Collection School Of Computing and Information Systems
We present a concept-based world building approach, realized in a system called VR Safari Park, which allows users to rapidly create and manipulate a world simulation. Conventional world building tools focus on the manipulation and arrangement of entities to set up the simulation, which is time consuming as it requires frequent view and entity manipulations. Our approach focuses on a far simpler mechanic, where users add virtual blocks which represent world entities (e.g. animals, terrain, weather, etc.) to a World Tree, which represents the simulation. In so doing, the World Tree provides a quick overview of the simulation, and users …
Gesture Recognition With Transparent Solar Cells, Dong Ma, Guohao Lan, Mahbub Hassan, Wen Hu, B. Mushfika Upama, Ashraf Uddin, Youseef, Moustafa
Gesture Recognition With Transparent Solar Cells, Dong Ma, Guohao Lan, Mahbub Hassan, Wen Hu, B. Mushfika Upama, Ashraf Uddin, Youseef, Moustafa
Research Collection School Of Computing and Information Systems
Transparent solar cell is an emerging solar energy harvesting technology that allows us to see through these cells. This revolutionary discovery is creating unique opportunities to turn any mobile device screen into solar energy harvester. In this paper, we consider the possibility of using such energy harvesting screens as a sensor to detect hand gestures. As different gestures impact the incident light on the screen in a different way, they are expected to create unique energy generation patterns for the transparent solar cell. Our goal is to recognize gestures by detecting these solar energy patterns. A key uncertainty we face …
Joint Representation Learning Of Cross-Lingual Words And Entities Via Attentive Distant Supervision, Yixin Cao, Lei Hou, Juanzi Li, Zhiyuan Liu, Chengjiang Li, Xu Chen, Tiansi Dong
Joint Representation Learning Of Cross-Lingual Words And Entities Via Attentive Distant Supervision, Yixin Cao, Lei Hou, Juanzi Li, Zhiyuan Liu, Chengjiang Li, Xu Chen, Tiansi Dong
Research Collection School Of Computing and Information Systems
Joint representation learning of words and entities benefits many NLP tasks, but has not been well explored in cross-lingual settings. In this paper, we propose a novel method for joint representation learning of cross-lingual words and entities. It captures mutually complementary knowledge, and enables cross-lingual inferences among knowledge bases and texts. Our method does not require parallel corpora, and automatically generates comparable data via distant supervision using multi-lingual knowledge bases. We utilize two types of regularizers to align cross-lingual words and entities, and design knowledge attention and crosslingual attention to further reduce noises. We conducted a series of experiments on …
Cross-Modal Recipe Retrieval With Stacked Attention Model, Jing-Jing Chen, Lei Pang, Chong-Wah Ngo
Cross-Modal Recipe Retrieval With Stacked Attention Model, Jing-Jing Chen, Lei Pang, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
Taking a picture of delicious food and sharing it in social media has been a popular trend. The ability to recommend recipes along will benefit users who want to cook a particular dish, and the feature is yet to be available. The challenge of recipe retrieval, nevertheless, comes from two aspects. First, the current technology in food recognition can only scale up to few hundreds of categories, which are yet to be practical for recognizing tens 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 …
Designing A Tangible Interface For Manager Awareness In Wilderness Search And Rescue, Brennan Jones, Anthony Tang, Carman Neustaedter, Alissa N. Antle, Elgin-Skye Mclaren
Designing A Tangible Interface For Manager Awareness In Wilderness Search And Rescue, Brennan Jones, Anthony Tang, Carman Neustaedter, Alissa N. Antle, Elgin-Skye Mclaren
Research Collection School Of Computing and Information Systems
We present a tangible interface for supporting wilderness search-and-rescue (SAR) managers in maintaining awareness of a large SAR incident, where there are numerous field teams searching for a lost person in a wilderness area. This interface consists of physical and digital representations of the search area and elements of the search activity (e.g., the locations of search teams, weather information, and clues from the field). It is intended to allow SAR managers to inspect information about the response and search area from different perspectives and aid them in planning by allowing them to physically manipulate the representations and explore the …
Geometry-Aware Similarity Learning On Spd Manifolds For Visual Recognition, Zhiwu Huang, R. Wang, X. Li, W. Liu, S. Shan, Gool L. Van, X Chen
Geometry-Aware Similarity Learning On Spd Manifolds For Visual Recognition, Zhiwu Huang, R. Wang, X. Li, W. Liu, S. Shan, Gool L. Van, X Chen
Research Collection School Of Computing and Information Systems
Symmetric positive definite (SPD) matrices have been employed for data representation in many visual recognition tasks. The success is mainly attributed to learning discriminative SPD matrices encoding the Riemannian geometry of the underlying SPD manifolds. In this paper, we propose a geometry-aware SPD similarity learning (SPDSL) framework to learn discriminative SPD features by directly pursuing a manifold-manifold transformation matrix of full column rank. Specifically, by exploiting the Riemannian geometry of the manifolds of fixed-rank positive semidefinite (PSD) matrices, we present a new solution to reduce optimization over the space of column full-rank transformation matrices to optimization on the PSD manifold, …
Predicting Visual Context For Unsupervised Event Segmentation In Continuous Photo-Streams, Ana García Del Molino, Joo-Hwee Lim, Ah-Hwee Tan
Predicting Visual Context For Unsupervised Event Segmentation In Continuous Photo-Streams, Ana García Del Molino, Joo-Hwee Lim, Ah-Hwee Tan
Research Collection School Of Computing and Information Systems
Segmenting video content into events provides semantic structures for indexing, retrieval, and summarization. Since motion cues are not available in continuous photo-streams, and annotations in lifelogging are scarce and costly, the frames are usually clustered into events by comparing the visual features between them in an unsupervised way. However, such methodologies are ineffective to deal with heterogeneous events, e.g. taking a walk, and temporary changes in the sight direction, e.g. at a meeting. To address these limitations, we propose Contextual Event Segmentation (CES), a novel segmentation paradigm that uses an LSTM-based generative network to model the photo-stream sequences, predict their …
Knowledge-Aware Multimodal Fashion Chatbot, Lizi Liao, You Zhou, Yunshan Ma, Richang Hong, Tat-Seng Chua
Knowledge-Aware Multimodal Fashion Chatbot, Lizi Liao, You Zhou, Yunshan Ma, Richang Hong, Tat-Seng Chua
Research Collection School Of Computing and Information Systems
Multimodal fashion chatbot provides a natural and informative way to fulfill customers’ fashion needs. However, making it ‘smart’ in generating substantive responses remains a challenging problem. In this paper, we present a multimodal domain knowledge enriched fashion chatbot. It forms a taxonomy-based learning module to capture the fine-grained semantics in images and leverages an endto-end neural conversational model to generate responses based on the conversation history, visual semantics, and domain knowledge. To avoid inconsistent dialogues, deep reinforcement learning method is used to further optimize the model.
Deep Understanding Of Cooking Procedure For Cross-Modal Recipe Retrieval, Jingjing Chen, Chong-Wah Ngo, Fu-Li Feng, Tat-Seng Chua
Deep Understanding Of Cooking Procedure For Cross-Modal Recipe Retrieval, Jingjing Chen, Chong-Wah Ngo, Fu-Li Feng, Tat-Seng Chua
Research Collection School Of Computing and Information Systems
Finding a right recipe that describes the cooking procedure for a dish from just one picture is inherently a difficult problem. Food preparation undergoes a complex process involving raw ingredients, utensils, cutting and cooking operations. This process gives clues to the multimedia presentation of a dish (e.g., taste, colour, shape). However, the description of the process is implicit, implying only the cause of dish presentation rather than the visual effect that can be vividly observed on a picture. Therefore, different from other cross-modal retrieval problems in the literature, recipe search requires the understanding of textually described procedure to predict its …
Mixed-Reality For Object-Focused Remote Collaboration, Martin Feick, Anthony Tang, Scott Bateman
Mixed-Reality For Object-Focused Remote Collaboration, Martin Feick, Anthony Tang, Scott Bateman
Research Collection School Of Computing and Information Systems
In this paper we outline the design of a mixed-reality system to support object-focused remote collaboration. Here, being able to adjust collaborators' perspectives on the object as well as understand one another's perspective is essential to support effective collaboration over distance. We propose a low-cost mixed-reality system that allows users to: (1) quickly align and understand each other's perspective; (2) explore objects independently from one another, and (3) render gestures in the remote's workspace. In this work, we focus on the expert's role and we introduce an interaction technique allowing users to quickly manipulation 3D virtual objects in space.
Wasserstein Divergence For Gans, J. Wu, Zhiwu Huang, J. Thoma, D. Acharya, Gool L. Van
Wasserstein Divergence For Gans, J. Wu, Zhiwu Huang, J. Thoma, D. Acharya, Gool L. Van
Research Collection School Of Computing and Information Systems
In many domains of computer vision, generative adversarial networks (GANs) have achieved great success, among which the family of Wasserstein GANs (WGANs) is considered to be state-of-the-art due to the theoretical contributions and competitive qualitative performance. However, it is very challenging to approximate the k-Lipschitz constraint required by the Wasserstein-1 metric (W-met). In this paper, we propose a novel Wasserstein divergence (W-div), which is a relaxed version of W-met and does not require the k-Lipschitz constraint. As a concrete application, we introduce a Wasserstein divergence objective for GANs (WGAN-div), which can faithfully approximate W-div through optimization. Under various settings, including …
A Vector Field Design Approach To Animated Transitions, Yong Wang, Daniel Archambault, Carlos E. Scheidegger, Huamin Qu
A Vector Field Design Approach To Animated Transitions, Yong Wang, Daniel Archambault, Carlos E. Scheidegger, Huamin Qu
Research Collection School Of Computing and Information Systems
Animated transitions can be effective in explaining and exploring a small number of visualizations where there are drastic changes in the scene over a short interval of time. This is especially true if data elements cannot be visually distinguished by other means. Current research in animated transitions has mainly focused on linear transitions (all elements follow straight line paths) or enhancing coordinated motion through bundling of linear trajectories. In this paper, we introduce animated transition design, a technique to build smooth, non-linear transitions for clustered data with either minimal or no user involvement. The technique is flexible and simple to …
Neural Collective Entity Linking, Yixin Cao, Lei Hou, Juanzi Li, Zhiyuan Liu
Neural Collective Entity Linking, Yixin Cao, Lei Hou, Juanzi Li, Zhiyuan Liu
Research Collection School Of Computing and Information Systems
Entity Linking aims to link entity mentions in texts to knowledge bases, and neural models have achieved recent success in this task. However, most existing methods rely on local contexts to resolve entities independently, which may usually fail due to the data sparsity of local information. To address this issue, we propose a novel neural model for collective entity linking, named as NCEL. NCEL applies Graph Convolutional Network to integrate both local contextual features and global coherence information for entity linking. To improve the computation efficiency, we approximately perform graph convolution on a subgraph of adjacent entity mentions instead of …
Covariance Pooling For Facial Expression Recognition, D. Acharya, Zhiwu Huang, D. Paudel, Gool L. Van
Covariance Pooling For Facial Expression Recognition, D. Acharya, Zhiwu Huang, D. Paudel, Gool L. Van
Research Collection School Of Computing and Information Systems
Classifying facial expressions into different categories requires capturing regional distortions of facial landmarks. We believe that second-order statistics such as covariance is better able to capture such distortions in regional facial features. In this work, we explore the benefits of using a manifold network structure for covariance pooling to improve facial expression recognition. In particular, we first employ such kind of manifold networks in conjunction with traditional convolutional networks for spatial pooling within individual image feature maps in an end-to-end deep learning manner. By doing so, we are able to achieve a recognition accuracy of 58.14% on the validation set …
Scale Impacts Elicited Gestures For Manipulating Holograms: Implications For Ar Gesture Design, Tran Pham, Jo Vermeulen, Anthony Tang, Lindsay Macdonald
Scale Impacts Elicited Gestures For Manipulating Holograms: Implications For Ar Gesture Design, Tran Pham, Jo Vermeulen, Anthony Tang, Lindsay Macdonald
Research Collection School Of Computing and Information Systems
Because gesture design for augmented reality (AR) remains idiosyncratic, people cannot necessarily use gestures learned in one AR application in another. To design discoverable gestures, we need to understand what gestures people expect to use. We explore how the scale of AR affects the gestures people expect to use to interact with 3D holograms. Using an elicitation study, we asked participants to generate gestures in response to holographic task referents, where we varied the scale of holograms from desktop-scale to room-scale objects. We found that the scale of objects and scenes in the AR experience moderates the generated gestures. Most …
Dimensionality's Blessing: Clustering Images By Underlying Distribution, Wen-Yan Lin, Jian-Huang Lai, Siying Liu, Yasuyuki Matsushita
Dimensionality's Blessing: Clustering Images By Underlying Distribution, Wen-Yan Lin, Jian-Huang Lai, Siying Liu, Yasuyuki Matsushita
Research Collection School Of Computing and Information Systems
Many high dimensional vector distances tend to a constant. This is typically considered a negative “contrastloss” phenomenon that hinders clustering and other machine learning techniques. We reinterpret “contrast-loss” as a blessing. Re-deriving “contrast-loss” using the law of large numbers, we show it results in a distribution’s instances concentrating on a thin “hyper-shell”. The hollow center means apparently chaotically overlapping distributions are actually intrinsically separable. We use this to develop distribution-clustering, an elegant algorithm for grouping of data points by their (unknown) underlying distribution. Distribution-clustering, creates notably clean clusters from raw unlabeled data, estimates the number of clusters for itself and …
'Is More Better?': Impact Of Multiple Photos On Perception Of Persona Profiles, Joni Salminen, Lene Nielsen, Soon-Gyo Jung, Jisun An, Haewoon Kwak, Bernard J. Jansen
'Is More Better?': Impact Of Multiple Photos On Perception Of Persona Profiles, Joni Salminen, Lene Nielsen, Soon-Gyo Jung, Jisun An, Haewoon Kwak, Bernard J. Jansen
Research Collection School Of Computing and Information Systems
In this research, we investigate if and how more photos than a single headshot can heighten the level of information provided by persona profiles. We conduct eye-tracking experiments and qualitative interviews with variations in the photos: a single headshot, a headshot and images of the persona in different contexts, and a headshot with pictures of different people representing key persona attributes. The results show that more contextual photos significantly improve the information end users derive from a persona profile; however, showing images of different people creates confusion and lowers the informativeness. Moreover, we discover that choice of pictures results in …
Perspective On And Re-Orientation Of Physical Proxies In Object-Focused Remote Collaboration, Martin Feick, Terrance Mok, Anthony Tang, Lora Oehlberg, Ehud Sharlin
Perspective On And Re-Orientation Of Physical Proxies In Object-Focused Remote Collaboration, Martin Feick, Terrance Mok, Anthony Tang, Lora Oehlberg, Ehud Sharlin
Research Collection School Of Computing and Information Systems
Remote collaborators working together on physical objects have difficulty building a shared understanding of what each person is talking about. Conventional video chat systems are insufficient for many situations because they present a single view of the object in a flattened image. To understand how this limited perspective affects collaboration, we designed the Remote Manipulator (ReMa), which can reproduce orientation manipulations on a proxy object at a remote site. We conducted two studies with ReMa, with two main findings. First, a shared perspective is more effective and preferred compared to the opposing perspective offered by conventional video chat systems. Second, …
Pageflip: Leveraging Page-Flipping Gestures For Efficient Command And Value Selection On Smartwatches, Teng Han, Jiannan Li, Khalad Hasan, Keisuke Nakamura, Randy Gomez, Ravin Balakrishnan, Pourang Irani
Pageflip: Leveraging Page-Flipping Gestures For Efficient Command And Value Selection On Smartwatches, Teng Han, Jiannan Li, Khalad Hasan, Keisuke Nakamura, Randy Gomez, Ravin Balakrishnan, Pourang Irani
Research Collection School Of Computing and Information Systems
Selecting an item of interest on smartwatches can be tedious and time-consuming as it involves a series of swipe and tap actions. We present PageFlip, a novel method that combines into a single action multiple touch operations such as command invocation and value selection for efficient interaction on smartwatches. PageFlip operates with a page flip gesture that starts by dragging the UI from a corner of the device. We first design PageFlip by examining its key design factors such as corners, drag directions and drag distances. We next compare PageFlip to a functionally equivalent radial menu and a standard swipe …
A Visual Interaction Cue Framework From Video Game Environments For Augmented Reality, Kody R. Dillman, Terrance Tin Hoi Mok, Anthony Tang, Lora Oehlberg, Alex Mitchell
A Visual Interaction Cue Framework From Video Game Environments For Augmented Reality, Kody R. Dillman, Terrance Tin Hoi Mok, Anthony Tang, Lora Oehlberg, Alex Mitchell
Research Collection School Of Computing and Information Systems
Based on an analysis of 49 popular contemporary video games, we develop a descriptive framework of visual interaction cues in video games. These cues are used to inform players what can be interacted with, where to look, and where to go within the game world. These cues vary along three dimensions: the purpose of the cue, the visual design of the cue, and the circumstances under which the cue is shown. We demonstrate that this framework can also be used to describe interaction cues for augmented reality applications. Beyond this, we show how the framework can be used to generatively …
Geocaching With A Beam: Shared Outdoor Activities Through A Telepresence Robot With 360 Degree Viewing, Yasamin Heshmat, Brennan Jones, Xiaoxuan Xiong, Carman Neustaedter, Anthony Tang, Bernhard E. Riecke, Lillian Yang
Geocaching With A Beam: Shared Outdoor Activities Through A Telepresence Robot With 360 Degree Viewing, Yasamin Heshmat, Brennan Jones, Xiaoxuan Xiong, Carman Neustaedter, Anthony Tang, Bernhard E. Riecke, Lillian Yang
Research Collection School Of Computing and Information Systems
People often enjoy sharing outdoor activities together such as walking and hiking. However, when family and friends are separated by distance it can be difficult if not impossible to share such activities. We explore this design space by investigating the benefits and challenges of using a telepresence robot to support outdoor leisure activities. In our study, participants participated in the outdoor activity of geocaching where one person geocached with the help of a remote partner via a telepresence robot. We compared a wide field of view (WFOV) camera to a 360° camera. Results show the benefits of having a physical …
The Way You Move: The Effect Of A Robot Surrogate Movement In Remote Collaboration, Martin Feick, Lora Oehlberg, Anthony Tang, André Miede, Ehud Sharlin
The Way You Move: The Effect Of A Robot Surrogate Movement In Remote Collaboration, Martin Feick, Lora Oehlberg, Anthony Tang, André Miede, Ehud Sharlin
Research Collection School Of Computing and Information Systems
In this paper, we discuss the role of the movement trajectory and velocity enabled by our tele-robotic system (ReMa) for remote collaboration on physical tasks. Our system reproduces changes in object orientation and position at a remote location using a humanoid robotic arm. However, even minor kinematics differences between robot and human arm can result in awkward or exaggerated robot movements. As a result, user communication with the robotic system can become less efficient, less fluent and more time intensive.
Enhanced Vireo Kis At Vbs 2018, Phuong Anh Nguyen, Yi-Jie Lu, Hao Zhang, Chong-Wah Ngo
Enhanced Vireo Kis At Vbs 2018, Phuong Anh Nguyen, Yi-Jie Lu, Hao Zhang, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
The VIREO Known-Item Search (KIS) system has joined the Video Browser Showdown (VBS) [1] evaluation benchmark for the first time in year 2017. With experiences learned, the second version of VIREO KIS is presented in this paper. Considering the color-sketch based retrieval, we propose a simple grid-based approach for color query. This method allows the aggregation of color distributions in video frames into a shot representation, and generates the pre-computed rank list for all available queries which reduces computational resources and favors a recommendation module. With focusing on concept based retrieval, we modify our multimedia event detection system at TRECVID …
Food Photo Recognition For Dietary Tracking: System And Experiment, Zhao-Yan Ming, Jingjing Chen, Yu Cao, Ciarán Forde, Chong-Wah Ngo, Tat Seng Chua
Food Photo Recognition For Dietary Tracking: System And Experiment, Zhao-Yan Ming, Jingjing Chen, Yu Cao, Ciarán Forde, Chong-Wah Ngo, Tat Seng Chua
Research Collection School Of Computing and Information Systems
Tracking dietary intake is an important task for health management especially for chronic diseases such as obesity, diabetes, and cardiovascular diseases. Given the popularity of personal hand-held devices, mobile applications provide a promising low-cost solution to tackle the key risk factor by diet monitoring. In this work, we propose a photo based dietary tracking system that employs deep-based image recognition algorithms to recognize food and analyze nutrition. The system is beneficial for patients to manage their dietary and nutrition intake, and for the medical institutions to intervene and treat the chronic diseases. To the best of our knowledge, there are …
Pagesense: Toward Stylewise Contextual Advertising Via Visual Analysis Of Web Pages, Tao Mei, Lusong Li, Xinmei Tian, Dacheng Tao, Chong-Wah Ngo
Pagesense: Toward Stylewise Contextual Advertising Via Visual Analysis Of Web Pages, Tao Mei, Lusong Li, Xinmei Tian, Dacheng Tao, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
The Internet has emerged as the most effective and a highly popular medium for advertising. Current contextual advertising platforms need publishers to manually change the original structure of their Web pages and predefine the position and style of embedded ads. Although publishers spend significant effort optimizing their Web page layout, a large number of Web pages contain noticeable blank regions. We present an innovative stylewise advertising platform for contextual advertising, called PageSense. The "style" of Web pages refers to the visual appearance of a Web page, such as color and layout. PageSense aims to associate style-consistent ads with Web pages. …