14075351
A Dynamic Bayesian Network Model for Autonomous 3D Reconstruction from a Single Indoor Image
When we look at a picture, our prior knowledge about the world allows us to resolve some of the ambiguities that are inherent to monocular vision, and thereby infer 3d information about the scene. We also recognize different objects, decide on their orientations, and identify how they are connected to their environment. Focusing on the problem of autonomous 3d reconstruction of indoor scenes, in this paper we present a dynamic Bayesian network model capable of resolving some of these ambiguities and recovering 3d information for many images. Our model assumes a "floorwall" geometry on the scene and is trained to recognize the floor-wall boundary in each column of the image. When the image is produced under perspective geometry, we show that this model can be used for 3d reconstruction from a single image. To our knowledge, this was the first monocular approach to automatically recover 3d reconstructions from single indoor images.
11497645
Spam Deobfuscation using a Hidden Markov Model
To circumvent spam filters, many spammers attempt to obfuscate their emails by deliberately misspelling words or introducing other errors into the text. For example viagra may be written vigra, or mortgage written m0rt gage. Even though humans have little difficulty reading obfuscated emails, most content-based filters are unable to recognize these obfuscated spam words. In this paper, we present a hidden Markov model for deobfuscating spam emails. We empirically demonstrate that our model is robust to many types of obfuscation including misspellings, incorrect segmentations (adding/removing spaces), and substitutions/insertions of non-alphabetic characters.
26133819
Multi-agent Technology as an enabler of Computer Supported Cooperative Work for the Mobile Workforce
This paper proposes an agent-based computer supported cooperative work system known as TeamWorker that enables cooperation between mobile workers for the execution of their jobs by providing services via conversational components (C-COMs). C-COMs, encapsulate agent interaction protocols, which can be dynamically plugged into participating agents. Furthermore, the intelligence and autonomy of agent technology is applied to overcome the barriers faced in mobile computing environments, such as difficulty in monitoring work progress, device diversity, need for multi-modal human agent interface, etc. Finally, we discuss how TeamWorker has been applied to a real mobile business process in a telecommunications company in the UK.
39638713
Robust H∞ fuzzy static output feedback control of T-S fuzzy systems with parametric uncertainties
This paper addresses robust H"~ fuzzy static output feedback control problem for T-S fuzzy systems with time-varying norm-bounded uncertainties. Sufficient conditions for synthesis of a fuzzy static output feedback controller for T-S fuzzy systems are derived in terms of a set of linear matrix inequalities (LMIs). In comparison with the existing literatures, the proposed approach not only simplifies the design procedure but also achieves a better H"~ performance. Three drawbacks existing in the previous papers such as coordinate transformation, same output matrices and BMI problem have been eliminated. The effectiveness of the proposed design method is demonstrated by an example for the control of a truck-trailer system.
7431488
An HMM-Based Threshold Model Approach for Gesture Recognition
A new method is developed using the hidden Markov model (HMM) based technique. To handle nongesture patterns, we introduce the concept of a threshold model that calculates the likelihood threshold of an input pattern and provides a confirmation mechanism for the provisionally matched gesture patterns. The threshold model is a weak model for all trained gestures in the sense that its likelihood is smaller than that of the dedicated gesture model for a given gesture. Consequently, the likelihood can be used as an adaptive threshold for selecting proper gesture model. It has, however, a large number of states and needs to be reduced because the threshold model is constructed by collecting the states of all gesture models in the system. To overcome this problem, the states with similar probability distributions are merged, utilizing the relative entropy measure. Experimental results show that the proposed method can successfully extract trained gestures from continuous hand motion with 93.14% reliability.
8884680
Using Segmented Objects in Ostensive Video Shot Retrieval
This paper presents a system for video shot retrieval in which shots are retrieved based on matching video objects using a combination of colour, shape and texture. Rather than matching on individual objects, our system supports sets of query objects which in total reflect the user's object-based information need. Our work also adapts to a shifting user information need by initiating the partitioning of a user's search into two or more distinct search threads, which can be followed by the user in sequence. This is an automatic process which maps neatly to the ostensive model for information retrieval in that it allows a user to place a virtual checkpoint on their search, explore one thread or aspect of their information need and then return to that checkpoint to then explore an alternative thread. Our system is fully functional and operational and in this paper we illustrate several design decisions we have made in building it.
16122349
Feature-Based Image Watermarking Method Using Scale-Invariant Keypoints
This paper addresses feature-based image watermarking methods for digital contents. Most previous watermarking algorithms suffer from geometric distortion attacks that desynchronize the location of the inserted watermark. In order to synchronize the watermark location, watermark synchronization should be performed. One solution for watermark synchronization is to use image features. This paper describes a feature-based watermarking method based on scale-invariant keypoints. We extract feature points from the scale-invariant keypoint extractor and then decompose feature points into a set of disjoint triangles. These triangles are watermarked by an additive spread-spectrum method on the spatial domain. We perform an intensive simulation in comparison with other feature-based watermarking methods using 100 test images. Results show that the proposed method is considerably robust against both geometric distortion attacks and signal processing attacks listed in Stirmark 3.1.