23025365
A structural approach to recognizing incomplete graphic objects
We propose a structural approach to recognizing incomplete graphic objects, which aims to recognize a graphic object before the user finishes drawing all its strokes. In our approach, we first create a spatial division tree (SDT) for the input object and then search for similar objects in the database of graphic object models based on this representation. Along with the SDT, an intersection-based relationship model is also proposed in our approach to describe the relationships among strokes. The experiment result has shown that our approach can significantly save user's input time for complex graphic objects. Moreover, it also proves that our approach can response to user's input in real-time and is independent of the user's drawing style.
140108792
Online Segmentation of Freehand Stroke by Dynamic Programming
12595607
Sketch Recognition Based on Topological Spatial Relationship
In recognition of composite graphic objects, topological spatial relationships of their components play an important role. Although most researchers focus on binary topological relationships, they cannot carry all information of the internal structure of the compound objects. Therefore, we introduce the ternary relationship, which is a complement to the binary relationship, to describe composite graphic objects. Moreover, we provide a constrained partial permutation algorithm based on both the binary and ternary topological spatial relationships to recognize the sketchy objects input by users in an online manner. Experimental results show that this approach is both efficient and effective for online composite graphics recognition in our sketch-based graphics input system–SmartSketchpad.
14575854
Query Translation Disambiguation as Graph Partitioning
Resolving ambiguity in the process of query translation is crucial to cross-language information retrieval when only a bilingual dictionary is available. In this paper we propose a novel approach for query translation disambiguation, named "spectral query translation model". The proposed approach views the problem of query translation disambiguation as a graph partitioning problem. For a given query, a weighted graph is first created for all possible translations of query words based on the co-occurrence statistics of the translation words. The best translation of the query is then determined by the most strongly connected component within the graph. The proposed approach distinguishes from previous approaches in that the translations of all query words are estimated simultaneously. Furthermore, translation probabilities are introduced in the proposed approach to capture the uncertainty in translating queries. Empirical studies with TREC datasets have shown that the spectral query translation model achieves a relative 20% -50% improvement in cross-language information retrieval, compared to other approaches that also exploit word co-occurrence statistics for query translation disambiguation.
14501514
Semi-supervised Multi-label Learning by Constrained Non-negative Matrix Factorization
We present a novel framework for multi-label learning that explicitly addresses the challenge arising from the large number of classes and a small size of training data. The key assumption behind this work is that two examples tend to have large overlap in their assigned class memberships if they share high similarity in their input patterns. We capitalize this assumption by first computing two sets of similarities, one based on the input patterns of examples, and the other based on the class memberships of the examples. We then search for the optimal assignment of class memberships to the unlabeled data that minimizes the difference between these two sets of similarities. The optimization problem is formulated as a constrained Non-negative Matrix Factorization (NMF) problem, and an algorithm is presented to efficiently find the solution. Compared to the existing approaches for multi-label learning, the proposed approach is advantageous in that it is able to explore both the unlabeled data and the correlation among different classes simultaneously. Experiments with text categorization show that our approach performs significantly better than several state-of-the-art classification techniques when the number of classes is large and the size of training data is small.
7010436
Dynamic layer management in superpeer architectures
Superpeer unstructured P2P systems have been found to be very effective by dividing the peers into two layers, superlayer and leaf-layer, in which message flooding is only conducted among superlayer and all leaf-peers are represented by corresponding superpeers. However, current superpeer systems do not employ any effective layer management schemes, so the transient and low-capacity peers are allowed to act as superpeers. Moreover, the lack of an appropriate size ratio maintenance mechanism on superlayer to leaf-layer makes the system's search performance far from being optimal. We present one workload model aimed at reducing the weighted overhead of a network. Using our proposed workload model, a network can determine an optimal layer size ratio between leaf-layer and superlayer. We then propose a dynamic layer management algorithm, DLM, which can maintain an optimal layer size ratio and adaptively elect and adjust peers between superlayer and leaf-layer. DLM is completely distributed in the sense that each peer decides to be a superpeer or a leaf-peer independently without global knowledge. DLM could effectively help a superpeer P2P system maintain the optimal layer size ratio and designate peers with relatively long lifetime and large capacities as superpeers, and the peers with short lifetime and low capacities as leaf-peers under highly dynamic network situations. We demonstrate that the quality of a superpeer system is significantly improved under the DLM scheme by comprehensive simulations.
9293300
Automatic registration of overlapping 3D point clouds using closest points
Abstract While the SoftAssign algorithm imposes a two-way constraint embedded into the deterministic annealing scheme and the EMICP algorithm imposes a one-way constraint, they represent the state of the art technique for the automatic registration of overlapping free form shapes. They both have a time complexity of O ( n 2 ). While the former has a space complexity also of O ( n 2 ), the latter has a space complexity of O ( n ). The heavy demand for computation and storage memory renders either the SoftAssign or EMICP algorithm to hardly operate on whole shapes with thousands of points. In this case, they often have to reduce the number of points to an order of 100s on the free form shapes to be registered. This paper proposes using closest points in conjunction with either the one-way or two-way constraint for the automatic registration of overlapping 3D point clouds and thus, combining the accuracy of both the SoftAssign and EMICP algorithms with the efficiency of the traditional ICP algorithm. A comparative study based on both synthetic data and real images has shown that the proposed algorithm does not significantly sacrifice accuracy and stability of either the SoftAssign or EMICP algorithm, but gains remarkable efficiency of the traditional ICP algorithm for the automatic registration of overlapping 3D point clouds. Since, the proposed algorithm is of general use and has an advantage of easy implementation, it is likely to become in the future a benchmark for the automatic registration of overlapping 3D point clouds.
5965790
On scalable and locality-aware web document sharing
We propose a scalable Web document sharing infrastructure model called Browsers-Aware Proxy Server. In this design, a proxy server connecting to a group of networked clients maintains an index file of data objects of all clients' browser caches. If a user request misses in its local browser cache and the proxy cache, the browsers-aware proxy server will search the index file attempting to find it in another client's browser cache before sending the request to an upper level proxy or the Web server. If such a request does hit in a remote client, this client will directly forward the data object to the requesting client; or the proxy server fetches the data object from this client and then forwards it to the requesting client. The contributions of this caching model are twofold. First, we show that the amount of sharable data in browser caches is significant and can be utilized for document sharing among clients to improve Web caching performance and scalability. Second, the browsers-aware model can effectively and further improve Web prefetching performance. The browsers-aware model and its supported prefetching technique build a strong locality-aware Internet environment to make Web accesses fast with low communication costs. Conducting trace-driven simulations, we show the effectiveness of the browsers-aware model, and its unique advantages to facilitate prefetching.