Total Variation Regularized Tensor RPCA for Background Subtraction from Compressive Measurements

Background subtraction has been a fundamental and widely studied task in video analysis, with a wide range of applications in video surveillance, teleconferencing and 3D modeling. Recently, motivated by compressive imaging, background subtraction from compressive measurements (BSCM) is becoming an active research task in video surveillance. In this paper, we propose a novel tensor-based robust PCA (TenRPCA) approach for BSCM by decomposing video frames into backgrounds with spatial-temporal correlations and foregrounds with spatio-temporal continuity in a tensor framework. In this approach, we use 3D total variation (TV) to enhance the spatio-temporal continuity of foregrounds, and Tucker decomposition to model the spatio-temporal correlations of video background. Based on this idea, we design a basic tensor RPCA model over the video frames, dubbed as the holistic TenRPCA model (H-TenRPCA). To characterize the correlations among the groups of similar 3D patches of video background, we further design a patch-group-based tensor RPCA model (PG-TenRPCA) by joint tensor Tucker decompositions of 3D patch groups for modeling the video background. Efficient algorithms using alternating direction method of multipliers (ADMM) are developed to solve the proposed models. Extensive experiments on simulated and real-world videos demonstrate the superiority of the proposed approaches over the existing state-of-the-art approaches.Comment: To appear in IEEE TI

Generation of a High-Visibility Four-Photon Entangled State and Realization of a Four-Party Quantum Communication Complexity Scenario

We obtain a four-photon polarization-entangled state with a visibility as high as (95.35\pm 0.45)% directly from a single down-conversion source. A success probability of (81.54\pm 1.38)% is observed by applying this entangled state to realize a four-party quantum communication complexity scenario (QCCS), which comfortably surpass the classical limit of 50%. As a comparison, two Einstein-Podolsky-Rosen (EPR) pairs are shown to implement the scenario with a success probability of (73.89\pm 1.33)%. This four-photon state can be used to fulfill decoherence-free quantum information processing and other advanced quantum communication schemes.Comment: REVTEX 4.0, 4 pages, 4 figures, 1 tabl

DiskANN++: Efficient Page-based Search over Isomorphic Mapped Graph Index using Query-sensitivity Entry Vertex

Given a vector dataset $\mathcal{X}$ and a query vector $\vec{x}_q$, graph-based Approximate Nearest Neighbor Search (ANNS) aims to build a graph index $G$ and approximately return vectors with minimum distances to $\vec{x}_q$ by searching over $G$. The main drawback of graph-based ANNS is that a graph index would be too large to fit into the memory especially for a large-scale $\mathcal{X}$. To solve this, a Product Quantization (PQ)-based hybrid method called DiskANN is proposed to store a low-dimensional PQ index in memory and retain a graph index in SSD, thus reducing memory overhead while ensuring a high search accuracy. However, it suffers from two I/O issues that significantly affect the overall efficiency: (1) long routing path from an entry vertex to the query's neighborhood that results in large number of I/O requests and (2) redundant I/O requests during the routing process. We propose an optimized DiskANN++ to overcome above issues. Specifically, for the first issue, we present a query-sensitive entry vertex selection strategy to replace DiskANN's static graph-central entry vertex by a dynamically determined entry vertex that is close to the query. For the second I/O issue, we present an isomorphic mapping on DiskANN's graph index to optimize the SSD layout and propose an asynchronously optimized Pagesearch based on the optimized SSD layout as an alternative to DiskANN's beamsearch. Comprehensive experimental studies on eight real-world datasets demonstrate our DiskANN++'s superiority on efficiency. We achieve a notable 1.5 X to 2.2 X improvement on QPS compared to DiskANN, given the same accuracy constraint.Comment: 15 pages including reference

Possible Influences on Ammonia Nitrogen Determination by Nessler's Reagent Spectrophotometry

Nessler's reagent spectrophotometry is the traditional method for ammonia nitrogen (NH3-N) determination, which is adopted in the national standard of the People's Republic of China (HJ 535-2009). In order to improve the accuracy of such method, possible influences, Nessler's Reagent preparation, pH value of the solution, metal ions, organic solvents and natural organic matters, on NH3-N determination were discussed. The results suggested that the method B, employing KI, HgI2 and NaOH, is preferred in Nessler's Reagent preparation. And the Nessler's Reagent Spectrophotometry may be executed over a wide pH range (4-11). The metal ions, organic solvents and natural organic matters have significant influences in NH3-N detection. Keywords Nessler's Reagent, Ammonia Nitrogen, pH, Metal Ion, Organic Solvent, Natural Organic Matter. DOI: 10.7176/JNSR/11-24-02 Publication date: December 31st 202