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Articles 1561 - 1590 of 1897

Full-Text Articles in Artificial Intelligence and Robotics

Designing And Comparing Multiple Portfolios Of Parameter Configurations For Online Algorithm Selection, Aldy Gunawan, Hoong Chuin Lau, Mustafa Misir Jun 2016

Designing And Comparing Multiple Portfolios Of Parameter Configurations For Online Algorithm Selection, Aldy Gunawan, Hoong Chuin Lau, Mustafa Misir

Research Collection School Of Computing and Information Systems

Algorithm portfolios seek to determine an effective set of algorithms that can be used within an algorithm selection framework to solve problems. A limited number of these portfolio studies focus on generating different versions of a target algorithm using different parameter configurations. In this paper, we employ a Design of Experiments (DOE) approach to determine a promising range of values for each parameter of an algorithm. These ranges are further processed to determine a portfolio of parameter configurations, which would be used within two online Algorithm Selection approaches for solving different instances of a given combinatorial optimization problem effectively. We …

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Strategic Planning For Setting Up Base Stations In Emergency Medical Systems, Supriyo Ghosh, Pradeep Varakantham Jun 2016

Strategic Planning For Setting Up Base Stations In Emergency Medical Systems, Supriyo Ghosh, Pradeep Varakantham

Research Collection School Of Computing and Information Systems

Emergency Medical Systems (EMSs) are an important component of public health-care services. Improving infrastructure for EMS and specifically the construction of base stations at the ”right” locations to reduce response times is the main focus of this paper. This is a computationally challenging task because of the: (a) exponentially large action space arising from having to consider combinations of potential base locations, which themselves can be significant; and (b) direct impact on the performance of the ambulance allocation problem, where we decide allocation of ambulances to bases. We present an incremental greedy approach to discover the placement of bases that …

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Modeling Autobiographical Memory In Human-Like Autonomous Agents, Di Wang, Ah-Hwee Tan, Chunyan Miao May 2016

Modeling Autobiographical Memory In Human-Like Autonomous Agents, Di Wang, Ah-Hwee Tan, Chunyan Miao

Research Collection School Of Computing and Information Systems

Although autobiographical memory is an important part of the human mind, there has been little effort on modeling autobiographical memory in autonomous agents. With the motivation of developing human-like intelligence, in this paper, we delineate our approach to enable an agent to maintain memories of its own and to wander in mind. Our model, named Autobiographical Memory-Adaptive Resonance Theory network (AM-ART), is designed to capture autobiographical memories, comprising pictorial snapshots of one’s life experiences together with the associated context, namely time, location, people, activity, and emotion. In terms of both network structure and dynamics, AM-ART coincides with the autobiographical memory …

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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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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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Simultaneous Optimization And Sampling Of Agent Trajectories Over A Network, Hala Mostafa, Akshat Kumar, Hoong Chuin Lau May 2016

Simultaneous Optimization And Sampling Of Agent Trajectories Over A Network, Hala Mostafa, Akshat Kumar, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

We study the problem of optimizing the trajectories of agents moving over a network given their preferences over which nodes to visit subject to operational constraints on the network. In our running example, a theme park manager optimizes which attractions to include in a day-pass to maximize the pass’s appeal to visitors while keeping operational costs within budget. The first challenge in this combinatorial optimization problem is that it involves quantities (expected visit frequencies of each attraction) that cannot be expressed analytically, for which we use the Sample Average Approximation. The second challenge is that while sampling is typically done …

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Approximate Inference Using Dc Programming For Collective Graphical Models, Duc Thien Nguyen, Akshat Kumar, Hoong Chuin Lau, Daniel Sheldon May 2016

Approximate Inference Using Dc Programming For Collective Graphical Models, Duc Thien Nguyen, Akshat Kumar, Hoong Chuin Lau, Daniel Sheldon

Research Collection School Of Computing and Information Systems

Collective graphical models (CGMs) provide a framework for reasoning about a population of independent and identically distributed individuals when only noisy and aggregate observations are given. Previous approaches for inference in CGMs work on a junction-tree representation, thereby highly limiting their scalability. To remedy this, we show how the Bethe entropy approximation naturally arises for the inference problem in CGMs. We reformulate the resulting optimization problem as a difference-of-convex functions program that can capture different types of CGM noise models. Using the concave-convex procedure, we then develop a scalable message-passing algorithm. Empirically, our approach is highly scalable and accurate for …

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Reinforcement Learning Framework For Modeling Spatial Sequential Decisions Under Uncertainty: (Extended Abstract), Truc Viet Le, Siyuan Liu, Hoong Chuin Lau May 2016

Reinforcement Learning Framework For Modeling Spatial Sequential Decisions Under Uncertainty: (Extended Abstract), Truc Viet Le, Siyuan Liu, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

We consider the problem of trajectory prediction, where a trajectory is an ordered sequence of location visits and corresponding timestamps. The problem arises when an agent makes sequential decisions to visit a set of spatial locations of interest. Each location bears a stochastic utility and the agent has a limited budget to spend. Given the agent's observed partial trajectory, our goal is to predict the remaining trajectory. We propose a solution framework to the problem considering both the uncertainty of utility and the budget constraint. We use reinforcement learning (RL) to model the underlying decision processes and inverse RL to …

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Robust Influence Maximization, Meghna Lowalekar, Pradeep Varakantham, Akshat Kumar May 2016

Robust Influence Maximization, Meghna Lowalekar, Pradeep Varakantham, Akshat Kumar

Research Collection School Of Computing and Information Systems

Influence Maximization is the problem of finding a fixed size set of nodes, which will maximize the expected number of influenced nodes in a social network. The number of influenced nodes is dependent on the influence strength of edges that can be very noisy. The noise in the influence strengths can be modeled using a random noise or adversarial noise model. It has been shown that all random processes that independently affect edges of the graph can be absorbed into the activation probabilities themselves and hence random noise can be captured within the independent cascade model. On the other hand, …

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Approximating The Performance Of A "Last Mile" Transportation System, Hai Wang, Amedeo Odoni May 2016

Approximating The Performance Of A "Last Mile" Transportation System, Hai Wang, Amedeo Odoni

Research Collection School Of Computing and Information Systems

The Last Mile Problem (LMP) refers to the provision of travel service from the nearest public transportation node to a home or office. We study the supply side of this problem in a stochastic setting, with batch demands resulting from the arrival of groups of passengers who request last-mile service at urban rail stations or bus stops. Closedform approximations are derived for the performance of Last Mile Transportations Systems as a function of the fundamental design parameters of such systems. An initial set of results is obtained for the case in which a fleet of vehicles of unit capacity provides …

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Personal Credit Profiling Via Latent User Behavior Dimensions On Social Media, Guangming Guo, Feida Zhu, Enhong Chen, Le Wu, Qi Liu, Yingling Liu, Minghui Qiu Apr 2016

Personal Credit Profiling Via Latent User Behavior Dimensions On Social Media, Guangming Guo, Feida Zhu, Enhong Chen, Le Wu, Qi Liu, Yingling Liu, Minghui Qiu

Research Collection School Of Computing and Information Systems

Consumer credit scoring and credit risk management have been the core research problem in financial industry for decades. In this paper, we target at inferring this particular user attribute called credit, i.e., whether a user is of the good credit class or not, from online social data. However, existing credit scoring methods, mainly relying on financial data, face severe challenges when tackling the heterogeneous social data. Moreover, social data only contains extremely weak signals about users’ credit label. To that end, we put forward a Latent User Behavior Dimension based Credit Model (LUBD-CM) to capture these small signals for personal …

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Patrol Scheduling In An Urban Rail Network, Hoong Chuin Lau, Zhi Yuan, Aldy Gunawan Apr 2016

Patrol Scheduling In An Urban Rail Network, Hoong Chuin Lau, Zhi Yuan, Aldy Gunawan

Research Collection School Of Computing and Information Systems

This paper presents the problem of scheduling security teams to patrol a mass rapid transit rail network of a large urban city. The main objective of patrol scheduling is to deploy security teams to stations of the network at varying time periods subject to rostering as well as security-related constraints. We present several mathematical programming models for different variants of this problem. To generate randomized schedules on a regular basis, we propose injecting randomness by varying the start time and break time for each team as well as varying the visit frequency and visit time for each station according to …

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Detection Of Bird Nests In Overhead Catenary System Images For High-Speed Rail, Xiao Wu, Ping Yuan, Qiang Peng, Chong-Wah Ngo, Jun-Yan He Mar 2016

Detection Of Bird Nests In Overhead Catenary System Images For High-Speed Rail, Xiao Wu, Ping Yuan, Qiang Peng, Chong-Wah Ngo, Jun-Yan He

Research Collection School Of Computing and Information Systems

The high-speed rail system provides a fast, reliable and comfortable means to transport large number of travelers over long distances. The existence of bird nests in overhead catenary system (OCS) can hazard to the safety of the high-speed rails, which will potentially result in long time delays and expensive damages. A vision-based intelligent inspection system capable of automatic detection of bird nests built on overhead catenary would avoid the damages and increase the reliability and punctuality, and therefore is attractive for a high-speed railway system. However, OCS images exhibit great variations with lighting changes, illumination conditions and complex backgrounds, which …

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Campus-Scale Mobile Crowd-Tasking: Deployment And Behavioral Insights, Thivya Kandappu, Archan Misra, Shih-Fen Cheng, Nikita Jaiman, Randy Tandriansiyah, Cen Chen, Hoong Chuin Lau, Deepthi Chander, Koustuv Dasgupta Mar 2016

Campus-Scale Mobile Crowd-Tasking: Deployment And Behavioral Insights, Thivya Kandappu, Archan Misra, Shih-Fen Cheng, Nikita Jaiman, Randy Tandriansiyah, Cen Chen, Hoong Chuin Lau, Deepthi Chander, Koustuv Dasgupta

Research Collection School Of Computing and Information Systems

Mobile crowd-tasking markets are growing at an unprecedented rate with increasing number of smartphone users. Such platforms differ from their online counterparts in that they demand physical mobility and can benefit from smartphone processors and sensors for verification purposes. Despite the importance of such mobile crowd-tasking markets, little is known about the labor supply dynamics and mobility patterns of the users. In this paper we design, develop and experiment with a realwporld mobile crowd-tasking platform, called TA$Ker. Our contributions are two-fold: (a) We develop TA$Ker, a system that allows us to empirically study the worker responses to push vs. pull …

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A Proactive Sampling Approach To Project Scheduling Under Uncertainty, Pradeep Varakantham, Na Fu, Hoong Chuin Lau Feb 2016

A Proactive Sampling Approach To Project Scheduling Under Uncertainty, Pradeep Varakantham, Na Fu, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

Uncertainty in activity durations is a key characteristic of many real world scheduling problems in manufacturing, logistics and project management. RCPSP/max with durational uncertainty is a general model that can be used to represent durational uncertainty in a wide variety of scheduling problems where there exist resource constraints. However, computing schedules or execution strategies for RCPSP/max with durational uncertainty is NP-hard and hence we focus on providing approximation methods in this paper. We pro- vide a principled approximation approach based on Sample Average Approximation (SAA) to compute proactive schedules for RCPSP/max with durational uncertainty. We further contribute an extension to …

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Achieving Stable And Fair Profit Allocation With Minimum Subsidy In Collaborative Logistics, Lucas Agussurja, Hoong Chuin Lau, Shih-Fen Cheng Feb 2016

Achieving Stable And Fair Profit Allocation With Minimum Subsidy In Collaborative Logistics, Lucas Agussurja, Hoong Chuin Lau, Shih-Fen Cheng

Research Collection School Of Computing and Information Systems

With the advent of e-commerce, logistics providers are faced with the challenge of handling fluctuating and sparsely distributed demand, which raises their operational costs significantly. As a result, horizontal cooperation are gaining momentum around the world. One of the major impediments, however, is the lack of stable and fair profit sharing mechanism. In this paper, we address this problem using the framework of computational cooperative games. We first present cooperative vehicle routing game as a model for collaborative logistics operations. Using the axioms of Shapley value as the conditions for fairness, we show that a stable, fair and budget balanced …

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Shortest Path Based Decision Making Using Probabilistic Inference, Akshat Kumar Feb 2016

Shortest Path Based Decision Making Using Probabilistic Inference, Akshat Kumar

Research Collection School Of Computing and Information Systems

We present a new perspective on the classical shortest path routing (SPR) problem in graphs. We show that the SPR problem can be recast to that of probabilistic inference in a mixture of simple Bayesian networks. Maximizing the likelihood in this mixture becomes equivalent to solving the SPR problem. We develop the well known Expectation-Maximization (EM) algorithm for the SPR problem that maximizes the likelihood, and show that it does not get stuck in a locally optimal solution. Using the same probabilistic framework, we then address an NP-Hard network design problem where the goal is to repair a network of …

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Robust Decision Making For Stochastic Network Design, Akshat Kumar, Arambam James Singh, Pradeep Varakantham, Daniel Sheldon Feb 2016

Robust Decision Making For Stochastic Network Design, Akshat Kumar, Arambam James Singh, Pradeep Varakantham, Daniel Sheldon

Research Collection School Of Computing and Information Systems

We address the problem of robust decision making for stochastic network design. Our work is motivated by spatial conservation planning where the goal is to take management decisions within a fixed budget to maximize the expected spread of a population of species over a network of land parcels. Most previous work for this problem assumes that accurate estimates of different network parameters (edge activation probabilities, habitat suitability scores) are available, which is an unrealistic assumption. To address this shortcoming, we assume that network parameters are only partially known, specified via interval bounds. We then develop a decision making approach that …

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Nlu Framework For Voice Enabling Non-Native Applications On Smart Devices, Soujanya Lanka, Deepika Panthania, Pooja Kushalappa, Pradeep Varakantham Feb 2016

Nlu Framework For Voice Enabling Non-Native Applications On Smart Devices, Soujanya Lanka, Deepika Panthania, Pooja Kushalappa, Pradeep Varakantham

Research Collection School Of Computing and Information Systems

Voice is a critical user interface on smart devices (wearables, phones, speakers, televisions) to access applications (or services) available on them. Unfortunately, only a few native applications (provided by the OS developer) are typically voice enabled in devices of today. Since, the utility of a smart device is determined more by the strength of external applications developed for the device, voice enabling non-native applications in a scalable, seamless manner within the device is a critical use case and is the focus of our work. We have developed a Natural Language Understanding (NLU) framework that uses templates supported by the application …

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Online Spatio-Temporal Matching In Stochastic And Dynamic Domains, Meghna Lowalekar, Pradeep Varakantham, Patrick Jaillet Feb 2016

Online Spatio-Temporal Matching In Stochastic And Dynamic Domains, Meghna Lowalekar, Pradeep Varakantham, Patrick Jaillet

Research Collection School Of Computing and Information Systems

Spatio-temporal matching of services to customers online is a problem that arises on a large scale in many domains associated with shared transportation (ex: taxis, ride sharing, super shuttles, etc.) and delivery services (ex: food, equipment, clothing, home fuel, etc.). A key characteristic of these problems is that matching of services to customers in one round has a direct impact on the matching of services to customers in the next round. For instance, in the case of taxis, in the second round taxis can only pick up customers closer to the drop off point of the customer from the first …

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Enabling Carrier Collaboration Via Order Sharing Double Auction: A Singapore Urban Logistics Perspective, Handoko Stephanus Daniel, Hoong Chuin Lau Jan 2016

Enabling Carrier Collaboration Via Order Sharing Double Auction: A Singapore Urban Logistics Perspective, Handoko Stephanus Daniel, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

A recent exploratory study on the collaborative urban logistics in Singapore suggests that cost reduction and privacy preservation are two main drivers that would motivate the participation of carriers in consolidating their last mile deliveries. With Singapore's mild restrictions on the vehicle types or the time windows for the last-mile delivery, we believe that with proper technology in place, an Urban Consolidation Center like the Tenjin Joint Distribution System in Fukuoka Japan may be implemented to achieve cost reduction with some degree of privacy preservation. Participating carriers keep their respective private orders and have the option to get their remaining …

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An Extended Study On Addressing Defender Teamwork While Accounting For Uncertainty In Attacker Defender Games Using Iterative Dec-Mdps, Eric Shieh, Albert Xin Jiang, Amulya Yadav, Pradeep Varakantham, Milind Tambe Jan 2016

An Extended Study On Addressing Defender Teamwork While Accounting For Uncertainty In Attacker Defender Games Using Iterative Dec-Mdps, Eric Shieh, Albert Xin Jiang, Amulya Yadav, Pradeep Varakantham, Milind Tambe

Research Collection School Of Computing and Information Systems

Multi-agent teamwork and defender-attacker security games are two areas that are currently receiving significant attention within multi-agent systems research. Unfortunately, despite the need for effective teamwork among multiple defenders, little has been done to harness the teamwork research in security games. The problem that this paper seeks to solve is the coordination of decentralized defender agents in the presence of uncertainty while securing targets against an observing adversary. To address this problem, we offer the following novel contributions in this paper: (i) New model of security games with defender teams that coordinate under uncertainty; (ii) New algorithm based on column …

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Coordinated Persuasion With Dynamic Group Formation For Collaborative Elderly Care, Budhitama Subagdja, Ah-Hwee Tan Dec 2015

Coordinated Persuasion With Dynamic Group Formation For Collaborative Elderly Care, Budhitama Subagdja, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

Ageing in place demands a new paradigm of inhouse caregiving allowing many aspects of daily lives to be tackled by smart appliances and technologies. The important challenges include the effective provision of recommendations by multiple parties of caregiver constituting changes of the user's behavior. In this multiagent environment, interdependencies between agents become major issues to tackle. This paper presents an approach of dynamic group formation for autonomous caregiving agents to collaborate in recommending different aspects of well-being. The approach supports the agents to regulate the timing of their recommendations, prevent conflicting messages, and cooperate to make more effective persuasions. A …

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Coordinated Persuasion With Dynamic Group Formation For Collaborative Elderly Care, Budhitama Subagdja, Ah-Hwee Tan Dec 2015

Coordinated Persuasion With Dynamic Group Formation For Collaborative Elderly Care, Budhitama Subagdja, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

Ageing in place demands a new paradigm of inhouse caregiving allowing many aspects of daily lives to be tackled by smart appliances and technologies. The important challenges include the effective provision of recommendations by multiple parties of caregiver constituting changes of the user’s behavior. In this multiagent environment, interdependencies between agents become major issues to tackle. This paper presents an approach of dynamic group formation for autonomous caregiving agents to collaborate in recommending different aspects of well-being. The approach supports the agents to regulate the timing of their recommendations, prevent conflicting messages, and cooperate to make more effective persuasions. A …

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Preface: Wi 2015, Ah-Hwee Tan, Yuefeng Li, Ee-Peng Lim, Jie Zhang, Dell Zhang, Julita Vassileva Dec 2015

Preface: Wi 2015, Ah-Hwee Tan, Yuefeng Li, Ee-Peng Lim, Jie Zhang, Dell Zhang, Julita Vassileva

Research Collection School Of Computing and Information Systems

This volume contains the papers selected for presentation at the 2015 IEEE/WIC/ACM International Conference on Web Intelligence (WI’15), which was held from 6 to 9 December 2015 in Singapore, a city which welcomes people from different parts of the world to work and play. Following the tradition of WI conference in previous years, WI’15 was collocated with 2015 IEEE/WIC/ACM International Conference on Intelligent Agent Technology (IAT’15). Both WI’15 and IAT’15 were sponsored by the IEEE Computer Society, Web Intelligence Consortium (WIC), Association for Computing Machinery (ACM), and the Memetic Computing Society. The two collocated conferences were hosted by the Joint …

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Preface Iat 2015, Ah-Hwee Tan, Yuefeng Li, Ee-Peng Lim, An Bo, Anita Raja, Sarvapali Ramchurn Dec 2015

Preface Iat 2015, Ah-Hwee Tan, Yuefeng Li, Ee-Peng Lim, An Bo, Anita Raja, Sarvapali Ramchurn

Research Collection School Of Computing and Information Systems

This volume contains the papers selected for presentation at the 2015 IEEE/WIC/ACM International Conference on Intelligent Agent Technology (IAT’15), which was held from 6 to 9 December 2015 in Singapore, a city which welcomes people from different parts of the world to work and play. Following the tradition of IAT conference in previous years, IAT’15 was collocated with 2015 IEEE/WIC/ACM International Conference on Web Intelligence (WI’15). Both WI’15 and IAT’15 were sponsored by the IEEE Computer Society, Web Intelligence Consortium (WIC), Association for Computing Machinery (ACM), and the Memetic Computing Society. The two collocated conferences were hosted by the Joint …

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Preface To Wi-Iat 2015 Workshops And Demo/Posters, Ah-Hwee Tan, Yuefeng Li Dec 2015

Preface To Wi-Iat 2015 Workshops And Demo/Posters, Ah-Hwee Tan, Yuefeng Li

Research Collection School Of Computing and Information Systems

This volume contains the papers selected for presentation at the workshops and demonstration/poster track as part of the 2015 IEEE/WIC/ACM International Conference on Web Intelligence (WI’15) and 2015 IEEE/WIC/ACM International Conference on Intelligent Agent Technology (IAT’15) held from 6 to 9 December 2015 in Singapore.

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Silver Assistants For Aging-In-Place, Di Wang, Budhitama Subagdja, Yilin Kang, Ah-Hwee Tan Dec 2015

Silver Assistants For Aging-In-Place, Di Wang, Budhitama Subagdja, Yilin Kang, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

In this demo, we present an assembly of silver assistants for supporting Aging-In-Place (AIP). The virtual agents are designed to serve around the clock to complement human care within the intelligent home environment. Residing in different platforms with ubiquitous access, the agents collaboratively provide holistic care to the elderly users. The demonstration is shown in a 3-D virtual home replicating a typical 5-room apartment in Singapore. Sensory inputs are stored in a knowledge base named Situation Awareness Model (SAM). Therefore, the capabilities of the agents can always be extended by expanding the knowledge defined in SAM. Using the simulation system, …

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Non-Intrusive Robust Human Activity Recognition For Diverse Age Groups, Di Wang, Ah-Hwee Tan, Daqing Zhang Dec 2015

Non-Intrusive Robust Human Activity Recognition For Diverse Age Groups, Di Wang, Ah-Hwee Tan, Daqing Zhang

Research Collection School Of Computing and Information Systems

—Many elderly prefer to live independently at their own homes. However, how to use modern technologies to ensure their safety presents vast challenges and opportunities. Being able to non-intrusively sense the activities performed by the elderly definitely has great advantages in various circumstances. Non-intrusive activity recognition can be performed using the embedded sensors in modern smartphones. However, not many activity recognition models are robust enough that allow the subjects to carry the smartphones in different pockets with unrestricted orientations and varying deviations. Moreover, to the best of our knowledge, no existing literature studied the difference between the youth and the …

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Oriented Object Proposals, Shengfeng He, Rynson W. H. Lau Dec 2015

Oriented Object Proposals, Shengfeng He, Rynson W. H. Lau

Research Collection School Of Computing and Information Systems

In this paper, we propose a new approach to generate oriented object proposals (OOPs) to reduce the detection error caused by various orientations of the object. To this end, we propose to efficiently locate object regions according to pixelwise object probability, rather than measuring the objectness from a set of sampled windows. We formulate the proposal generation problem as a generative probabilistic model such that object proposals of different shapes (i.e., sizes and orientations) can be produced by locating the local maximum likelihoods. The new approach has three main advantages. First, it helps the object detector handle objects of different …

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