RESUMO
This paper investigates the signal to interference plus noise ratio (SINR) performance of the imaging laser radar (ILR) system operating at a wavelength of 905 nm using an avalanche photodiode array under the fog condition. We analysis the glow image of the light source, which is formed by the laser spot irradiated on a standard Lambertian target. Based on the proposed theoretical model, we determine the interference due to the glow inter-channel crosstalk under different fog conditions for a targeted channel. We show that, for transmission spans less than several tens of meters the interference due to glow crosstalk is higher than the fog (light to medium) induced losses. However, for a link range longer than 21 m the glow crosstalk induced interference is lower than the heavy fog induced attenuation. The proposed system performance is evaluated by developing an experimental test bed and using a dedicated indoor atmospheric chamber under homogeneously controlled fog conditions. We show that, under different fog conditions experimental results for changing SINR levels match well with the predicted data. The results shown can be used for design optimization of the ILR system when operated under fog conditions.
RESUMO
Textual data such as tags, sentence descriptions are combined with visual cues to reduce the semantic gap for image retrieval applications in today's Multimodal Image Retrieval (MIR) systems. However, all tags are treated as equally important in these systems, which may result in misalignment between visual and textual modalities during MIR training. This will further lead to degenerated retrieval performance at query time. To address this issue, we investigate the problem of tag importance prediction, where the goal is to automatically predict the tag importance and use it in image retrieval. To achieve this, we first propose a method to measure the relative importance of object and scene tags from image sentence descriptions. Using this as the ground truth, we present a tag importance prediction model to jointly exploit visual, semantic and context cues. The Structural Support Vector Machine (SSVM) formulation is adopted to ensure efficient training of the prediction model. Then, the Canonical Correlation Analysis (CCA) is employed to learn the relation between the image visual feature and tag importance to obtain robust retrieval performance. Experimental results on three real-world datasets show a significant performance improvement of the proposed MIR with Tag Importance Prediction (MIR/TIP) system over other MIR systems.
RESUMO
In this paper, we present a compressed-domain video retargeting solution that operates without compromising the resizing quality. Existing video retargeting methods operate in the spatial (or pixel) domain. Such a solution is not practical if it is implemented in mobile devices due to its large memory requirement. In the proposed solution, each component of the retargeting system is designed to exploit the low-level compressed domain features extracted from the coded bit stream. For example, motion information is obtained directly from motion vectors. An efficient column shape mesh deformation is employed to solve the difficulty of sophisticated quad-shape mesh deformation in the compressed domain. The proposed solution achieves comparable (or slightly better) visual quality performance as compared with several state-of-the-art pixel-domain retargeting methods at lower computational and memory costs, making content-aware video resizing both scalable and practical in real-world applications.
RESUMO
We examined risk factors associated with Necator americanus infection among persons aged > or =50 years in Hainan Province, People's Republic of China. Age and sex made the most important contributions to the variation in infection intensity (28%-30%), with age alone responsible for 27% of this variation. When stratified by 20-year age intervals, the influence of shared residence was 23% for persons aged > or =50 years and 27% for those aged <20 years, who had the highest and lowest levels of infection intensity, respectively. This points to shared residence as a means of capturing the complex relationship between aging and shared socioeconomic, environmental, and behavioral factors that influence transmission of Necator infection. None of the other 26 personal or 32 household risk factors were found to be significant. The importance of aging in Necator infection reveals an emerging public health problem among the elderly population of developing countries.
