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In recent years, VLAD has become a popular method which encoding powerful local descriptors to the compact representations. By using this approach, an image can be represented by just a few dozen bytes while preserving excellent retrieval results after the dimensionality reduction and compression. However, throwing away the spatial information is one of the biggest weaknesses of VLAD. This paper adopts...
Local features have been widely used in many computer vision related researches, such as near-duplicate image and video retrieval. However, the storage and query cost of local features become prohibitive on large-scale database. In this paper, we propose a representative local features mining method to generate a compact but more effective feature subset. First, we do an unsupervised annotation for...
Dynamics are inherent characteristics of batch processes, and the dynamic behavior may exist not only within a batch run, but also from batch to batch. Recently, a two-dimensional (2D) autoregressive model has been used to formulate the dynamic batch processes framework. For such two-dimensional (2D) dynamic batch monitoring, a statistical online process monitoring scheme is presented in this paper...
This paper presents a novel algorithm for fast and robust video copy detection. The idea is to use local features to estimate the copy transformation parameters first and then use the estimated parameters to guide the global-feature-based matching at a later stage. It is based on the fact that the copy transformations generally remain unchanged in a continuous video clip even in the whole video. Local-feature-based...
Locality Sensitive Hashing (LSH) is proposed to construct indexes for high-dimensional approximate similarity search. Multi-Probe LSH (MPLSH) is a variation of LSH which can reduce the number of hash tables. Based on the idea of MPLSH, this paper proposes a novel probability model and a query-adaptive algorithm to generate the optimal multi-probe sequence for range queries. Our probability model takes...
Constructing effective and efficient indexes for explosive growing multimedia data is a very challenging problem. To solve the problem, Haghani et al. provide a distributed similarity search method in high dimensions using Locality Sensitive Hashing. However, their method needs to estimate a global parameter on the whole dataset beforehand. It is impractical for a large-scale dynamical dataset. This...
Motion estimation is always regarded as the most time consuming module in video coding, and many fast motion estimation algorithms have been proposed to speed-up it. However one fact that motion regions need more complex search whereas still regions does not instead is often ignored. On the other hand, the analysis of the distribution of motion vector difference shows that the predicted motion vector...
Spatial matching for object retrieval is often time-consuming and susceptible to viewpoint changes. To address this problem, we propose a novel spatial matching method and implement it on modern GPU in parallel. Unlike previous spatial matching methods, in which the affine transformation estimation is based on the gravity vector assumption, our method abandons this strong assumption by matching the...
An image edge detection method of river regime is presented for river model images. This method of self-adaptive thresholding Canny edge detection can extracts the edges of river regime automatically. It not only inherits the advantages of traditional Canny Algorithm, but also uses the improved maximum variance ratio method to calculate the values of Canny gradient threshold self-adaptively. And on...
In a pervasive computing environment, the personalized recommender system incorporates contexts into recommendation and becomes a multiple dimensional decision expert system. In this paper, we present DFre, a distributed fuzzy reasoning engine for personalization recommendation. With difference from those existing rule-based systems, the DFre puts an emphasis on the distribution of the recommendation...
In a personalized recommender system of a ubiquitous computing environment, the decision on recommendation depends on some uncertain factors. Fuzzy system has an ability of solving the reasoning uncertainty, and gets widely used in the context awareness based personalized recommender system. In this paper, we present a fuzzy reasoning model based on the Fuzzy Petri Net. The model considers the requirements...
This paper presents a novel service discovery framework for ubiquitous computing called hierarchical ubiquitous computing service discovery framework (HUCSDF). HUCSDF offers a more flexible and scalable architecture which can combine the local services with remote services. Based on the novel architecture, HUCSDF possesses some useful characteristics such as supporting migration of user's personal...
This paper presents a novel service discovery framework for ubiquitous computing called Ubiquitous Computing Service Discovery Framework (UCSDF). UCSDF offers a more flexible and scalable architecture which can combine the local services with remote services. That characteristic makes UCSDF different from many other service discovery frameworks and more adaptive to ubiquitous computing environments.
This paper proposes the peer-to-peer context sharing model (PCSM) which is a ubiquitous computing oriented peer-to-peer context sharing model. Owing to the distribution and limit of resources of the mobile ubiquitous network, the PCSM model constructs a context management framework based on the mechanism of registration-query. Through designing the broadcast messages for available terminals discovery...
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