Efficient and effective state-based framework for news video retrieval

In this paper, an efficient and effective framework is proposed for news video retrieval. Firstly, the 64-dimensional colour histogram is extracted as the feature vector. Then the pair quantizer is adopted to transfer the news video retrieval problem into multi-dimensional string matching problem, which conduces to the efficiency to the framework. Secondly, a new measurement named ‘optimal temporal common subsequence’, which distinguishes the difference caused by rich temporal characteristics including temporal order, temporal duration and temporal gap, is designed to match state-sequence, followed by the point & interval-based formal characterization of time-series and state-sequences. Thirdly, we tested the proposed measurement on news video retrieval. The performance shows the proposed algorithm is more effective for news video retrieval

Notch signalling and its role in corneal epithelium survival and differentiation

To elucidate mechanism of corneal epithelial cell differentiation, proliferation and stratification is crucial for maintaining epithelial cell homeostasis, manipulating corneal wound healing and developing therapeutic strategy for treatment ocular surface diseases. The Notch signalling system regulates cell fate decisions and cell function. In human, there are four Notch receptors, Notch 1 to 4, and five ligands, including Deltal, 3, 4, Jaggedl, 2. Activation of Notch upon ligand binding is accompanied by proteolytic processing regulated by gamma-secretase. This study aimed to determine whether the components of the Notch are expressed in the human corneal epithelial cells and the role of Notch signalling in corneal epithelial homeostasis, stratification and wound healing. METHODS Immunohistochemistry was employed for the localisation of the Notch receptors and their ligands in fresh human cornea and embryonic chicken cornea. Gene expression of Notch receptors and their ligands was determined using reverse transcriptase- polymerase chain reaction (RT-PCR) in cultured human corneal epithelial cells and keratocytes. Western Blotting analysis, immunocytochemistry in the presence or absence gamma-secretase inhibitor and Jaggedl were used to correlate Notch with Ki67 (a marker of cell proliferation) and cytokeratin 3 (a marker of cell differentiation) expressions for a functional study of proliferation and differentiation in corneal epithelial cells. The co-culture model with amniotic membrane and an organ culture model of intact rat cornea were used to investigate the function of Notch in corneal epithelial cell stratification. Also, an organ culture of wounded cornea was used to study the role of Notch in corneal epithelial and stromal wound healing. RESULTS Immunohistochemical results showed that Notch 1 and Notch2 expressed throughout the corneal epithelium in superficial and suprabasal layers. Delta 1 and Jaggedl appeared to be expressed throughout all cell layers of the corneal epithelium. The expression of activated Notch 1, Notch2 and Ki67 was decreased and cytokeratin 3 was increased after the Notch pathway was blocked by a gamma-secretase inhibitor. In contrast, activation of Notch pathway by Jaggedl induced the increase of the expression of activated Notch 1, Notch2 and Ki67 and decreased the expression of cytokeratin 3. The corneal stratification was inhibited by activation of Notch. In wound healing study, Notch inhibited the wound repair at late stage. In addition, the expression pattern of Notch was exhibited in developmental embryonic chicken cornea. CONCLUSIONS Notch suppresses differentiation and stratification in corneal epithelium. Activation of Notch results the retardation of corneal wound repair. Notch signalling system plays a pivotal role in maintenance of corneal epithelial cell homeostasis and wound healing

Flare-Aware Cross-modal Enhancement Network for Multi-spectral Vehicle Re-identification

Multi-spectral vehicle re-identification aims to address the challenge of identifying vehicles in complex lighting conditions by incorporating complementary visible and infrared information. However, in harsh environments, the discriminative cues in RGB and NIR modalities are often lost due to strong flares from vehicle lamps or sunlight, and existing multi-modal fusion methods are limited in their ability to recover these important cues. To address this problem, we propose a Flare-Aware Cross-modal Enhancement Network that adaptively restores flare-corrupted RGB and NIR features with guidance from the flare-immunized thermal infrared spectrum. First, to reduce the influence of locally degraded appearance due to intense flare, we propose a Mutual Flare Mask Prediction module to jointly obtain flare-corrupted masks in RGB and NIR modalities in a self-supervised manner. Second, to use the flare-immunized TI information to enhance the masked RGB and NIR, we propose a Flare-Aware Cross-modal Enhancement module that adaptively guides feature extraction of masked RGB and NIR spectra with prior flare-immunized knowledge from the TI spectrum. Third, to extract common informative semantic information from RGB and NIR, we propose an Inter-modality Consistency loss that enforces semantic consistency between the two modalities. Finally, to evaluate the proposed FACENet in handling intense flare, we introduce a new multi-spectral vehicle re-ID dataset, called WMVEID863, with additional challenges such as motion blur, significant background changes, and particularly intense flare degradation. Comprehensive experiments on both the newly collected dataset and public benchmark multi-spectral vehicle re-ID datasets demonstrate the superior performance of the proposed FACENet compared to state-of-the-art methods, especially in handling strong flares. The code and dataset will be released soon

Character-angle based video annotation

A video annotation system includes clips organization, feature description and pattern determination. This paper aims to present a system for basketball zone-defence detection. Particularly, a character-angle based descriptor for feature description is proposed. The well-performed experimental results in basketball zone-defence detection demonstrate that it is robust for both simulations and real-life cases, with less sensitivity to the distribution caused by local translation of subprime defenders. Such a framework can be easily applied to other team-work sports

Temporal pattern recognition in video clips detection

Temporal representation and reasoning plays an important role in Data Mining and Knowledge Discovery, particularly, in mining and recognizing patterns with rich temporal information. Based on a formal characterization of time-series and state-sequences, this paper presents the computational technique and algorithm for matching state-based temporal patterns. As a case study of real-life applications, zone-defense pattern recognition in basketball games is specially examined as an illustrating example. Experimental results demonstrate that it provides a formal and comprehensive temporal ontology for research and applications in video events detection

Immediate Antiretroviral Therapy Decreases Mortality Among Patients With High CD4 Counts in China: A Nationwide, Retrospective Cohort Study.

BackgroundClinical trials have demonstrated that immediate initiation of antiretroviral therapy (ART) reduces AIDS-related morbidity and mortality. We tested the hypothesis that initiating ART ≤30 days after human immunodeficiency virus (HIV) diagnosis would be associated with reduced mortality among people living with HIV (PLWH) with CD4 counts >500 cells/μL.MethodsPLWH enrolled in the Chinese National HIV Information System between January 2012 and June 2014 with CD4 counts >500 cells/μL were followed for 12 months. Cox proportional hazards model was used to determine hazard ratios (HRs) for PLWH who initiated ART after HIV diagnosis. ART initiation was treated as a time-dependent variable.ResultsWe enrolled 34581 PLWH with CD4 >500 cells/μL; 1838 (5.3%) initiated ART ≤30 days after diagnosis (immediate ART group), and 19 deaths were observed with a mortality rate of 1.04 per 100 person-years (PY). Fifty-eight deaths were documented among the 5640 PLWH in the delayed ART group with a mortality rate of 2.25 per 100 PY. There were 713 deaths among the 27103 PLWH in the no ART group with a mortality rate of 2.39 per 100 PY. After controlling for potential confounding factors, ART initiation at ≤30 days (adjusted HR, 0.37 [95% confidence interval, .23-.58]) was a statistically significant protective factor.ConclusionsWe found that immediate ART is associated with a 63% reduction in overall mortality among PLWH with CD4 counts >500 cells/μL in China, supporting the recommendation to initiate ART immediately following HIV diagnosis

A novel distance learning for elastic cross-modal audio-visual matching

In this work we propose a novel network formulation for joint representation of cross-modal audio and visual information base on metric learning. We employ a distance learning framework as a training procedure. For this purpose we introduce an elastic matching network (EmNet) and a novel loss function to learn the shared latent space representation of multi-modal information. The elastic matching network is capable of matching given face image (or audio voice clip) from diverse number of audio clips (or face images). We quantitatively and qualitatively evaluate the purposed approach on the standard audio-visual matching evaluation dataset, the overlap of VoxCeleb and VGGFace by both multi-way and binary audio-visual matching tasks. The promising performance comparing to the existing methods verifies the effectiveness of the proposed approach, which yields to a new state-of-the-art for cross-modal audio-visual matching

Manifold ranking weighted local maximal occurrence descriptor for person re-identification

Person re-identification is an important task of matching pedestrians across non-overlapping camera views. In this paper, we exploit a weighted feature descriptor for person re-identification.We firstly compute the weights on the superpixel level via graph-based manifold ranking algorithm, then integrate the computed weights into a patch-based feature descriptor, named local maximal occurrence. Finally, the weighted descriptors are fed into a top-push distance learning to mitigate the cross-view gaps. We evaluate the proposed method on three benchmark datasets iLIDS-VID, PRID 450S and VIPeR. The promising experimental results demonstrate the effectiveness of the proposed method comparing with the state-of-the-arts