36919902
Motion planning with uncertainty
We present a general framework for motion planning of robots in the presence of obstacles and other robots. We use variational calculus and optimization to find optimal open loop and closed loop plans in the presence of uncertainty. The plans are based on world models with set-valued uncertainty associated with the positions and shape of the obstacles. The open loop plans are generated by an efficient method that allows successive refinements of a nominal motion plan and accommodates finer levels of granularity as additional information becomes available. The closed loop plans are control policies that are based on given sensor models. The optimal plan is a control policy that performs the best in the worst-case situation. We discuss how the open loop and closed loop plans can be viewed as optimal strategies in the framework of two-person, zero-sum, non-cooperative games.
16979558
Region-based relevance feedback in image retrieval
Relevance feedback and region-based representation of images are two effective ways to improve accuracy in content-based image retrieval. We propose a novel relevance feedback approach based on region representation. It can be considered as a special case of the query point movement method in region-based image retrieval. By assembling all the segmented regions of positive examples together and resizing the regions to emphasize the latest positive examples, we form a composite image as the optimal query. A region-based image similarity measure is used to calculate the distance between the optimal query and an image in the database. An incremental clustering technique is also considered to improve the retrieval efficiency. Experimental results show that the proposed approach is effective in improving the performance of content-based image retrieval systems.
15756415
Assembly Sequence Planning
The sequence of mating operations that can be carried out to assemble a group of parts is constrained by the geometric and mechanical properties of the parts, their assembled configuration, and the stability of the resulting subassemblies. An approach to representation and reasoning about these sequences is described here and leads to several alternative explicit and implicit plan representations. The Pleiades system will provide an interactive software environment for designers to evaluate alternative systems and product designs through their impact on the feasibility and complexity of the resulting assembly sequences.
16669804
An effective region-based image retrieval framework
We present a region-based image retrieval framework that integrates efficient region-based representation in terms of storage and retrieval and effective on-line learning capability. The framework consists of methods for image segmentation and grouping, indexing using modified inverted file, relevance feedback, and continuous learning. By exploiting a vector quantization method, a compact region-based image representation is achieved. Based on this representation, an indexing scheme similar to the inverted file technology is proposed. In addition, it supports relevance feedback based on the vector model with a weighting scheme. A continuous learning strategy is also proposed to enable the system to self improve. Experimental results on a database of 10,000 general-purposed images demonstrate the efficiency and effectiveness of the proposed framework.
2491447
Unsupervised image segmentation using local homogeneity analysis
In this paper, a novel method is presented for unsupervised image segmentation based on local homogeneity analysis. First, a criterion for homogeneity of a certain pattern is proposed. Applying the criterion to local windows in the original image results in the "H-image". The high and low values of the H-image correspond to possible region boundaries and region interiors respectively. Then, a region growing method is used to segment the image based on the H-image. Finally, visually similar regions are merged together to avoid over-segmentation. Experimental results on real images show the effectiveness and robustness of the method.
14763506
Real-time voxelization for complex polygonal models
In this paper, we present an efficient voxelization algorithm for complex polygonal models by exploiting newest programmable graphics hardware. We first convert the model into three discrete voxel spaces according to its surface orientation. The resultant voxels are encoded as 2D textures and stored in three intermediate sheet buffers called directional sheet buffers. These buffers are finally synthesized into one worksheet, which records the volumetric representation of the target. The whole algorithm traverses the geometric model only once and is accomplished entirely in GPU (graphics processing unit), achieving real-time frame rate for models with up to 2 million triangles.
1573162
Automated annotation of human faces in family albums
Automatic annotation of photographs is one of the most desirable needs in family photograph management systems. In this paper, we present a learning framework to automate the face annotation in family photograph albums. Firstly, methodologies of content-based image retrieval and face recognition are seamlessly integrated to achieve automated annotation. Secondly, face annotation is formulated in a Bayesian framework, in which the face similarity measure is defined as maximum a posteriori (MAP) estimation. Thirdly, to deal with the missing features, marginal probability is used so that samples which have missing features are compared with those having the full feature set to ensure a non-biased decision. The experimental evaluation has been conducted within a family album of few thousands of photographs and the results show that the proposed approach is effective and efficient in automated face annotation in family albums.
17695045
A Multi-Agent Approach for Peer-to-Peer Based Information Retrieval System
This paper develops and analyzes distributed search techniques for use in a peer-to-peer (P2P) network-based Information Retrieval (IR) system. In the absence of a centralized mediator with global knowledge that directs requests to appropriate agents, agents must cooperate to forward the queries among themselves so as to find appropriate agents, and return and merge the results in order to fulfill the information retrieval task in a distributed environment. In our approach, the agent society is connected through an agent-view structure maintained by each agent. Initially, the agent-view structures are formed by agents connecting to each other randomly. However, we show that such an approach can be significantly enhanced by dynamically reorganizing the underlying agent-view topology and deploying contextsensitive distributed search algorithms. Experimental results indicate that appropriate organizational structures and distributed search mechanisms can have a positive influence on system performance.
13845864
On the interaction between overlay routing and underlay routing
In this paper, we study the interaction between overlay routing and traffic engineering (TE) in a single autonomous system (AS). We formulate this interaction as a two-player non-cooperative non-zero sum game, where the overlay tries to minimize the delay of its traffic and the TE's objective is to minimize network cost. We study a Nash routing game with best-reply dynamics, in which the overlay and TE have equal status, and take turns to compute their optimal strategies based on the response of the other player in the previous round. We prove the existence, uniqueness and global stability of Nash equilibrium point (NEP) for a simple network. For general networks, we show that the selfish behavior of an overlay can cause huge cost increases and oscillations to the whole network. Even worse, we have identified cases, both analytically and experimentally, where the overlay's cost increases as the Nash routing game proceeds even though the overlay plays optimally based on TE's routing at each round. Experiments are performed to verify our analysis.
14971297
Non-uniform Differential Mesh Deformation
In this paper, we propose a novel mesh deformation approach via manipulating differential properties non-uniformly. Guided by user-specified material properties, our method can deform the surface mesh in a non-uniform way while previous deformation techniques are mainly designed for uniform materials. The non-uniform deformation is achieved by material-dependent gradient field manipulation and Poisson-based reconstruction. Comparing with previous material-oblivious deformation techniques, our method supplies finer control of the deformation process and can generate more realistic results. We propose a novel detail representation that transforms geometric details between successive surface levels as a combination of dihedral angles and barycentric coordinates. This detail representation is similarity-invariant and fully compatible with material properties. Based on these two methods, we implement a multiresolution deformation tool, which allows the user to edit a mesh inside a hierarchy in a material-aware manner. We demonstrate the effectiveness and robustness of our methods by several examples with real-world data.