Semantic feature-based visual attention model for pedestrian detection

Objective
Pedestrian detection under video surveillance systems has always been a hot topic in computer vision research. These systems are widely used in train stations, airports, large commercial plazas, and other public places. However, pedestrian detection remains difficult because of complex backgrounds. Given its development in recent years, the visual attention mechanism has attracted increasing attention in object detection and tracking research, and previous studies have achieved substantial progress and breakthroughs. We propose a novel pedestrian detection method based on the semantic features under the visual attention mechanism.
Method
The proposed semantic feature-based visual attention model is a spatial-temporal model that consists of two parts: the static visual attention model and the motion visual attention model. The static visual attention model in the spatial domain is constructed by combining bottom-up with top-down attention guidance. Based on the characteristics of pedestrians, the bottom-up visual attention model of Itti is improved by intensifying the orientation vectors of elementary visual features to make the visual saliency map suitable for pedestrian detection. In terms of pedestrian attributes, skin color is selected as a semantic feature for pedestrian detection. The regional and Gaussian models are adopted to construct the skin color model. Skin feature-based visual attention guidance is then proposed to complete the top-down process. The bottom-up and top-down visual attentions are linearly combined using the proper weights obtained from experiments to construct the static visual attention model in the spatial domain. The spatial-temporal visual attention model is then constructed via the motion features in the temporal domain. Based on the static visual attention model in the spatial domain, the frame difference method is combined with optical flowing to detect motion vectors. Filtering is applied to process the field of motion vectors. The saliency of motion vectors can be evaluated via motion entropy to make the selected motion feature more suitable for the spatial-temporal visual attention model.
Result
Standard datasets and practical videos are selected for the experiments. The experiments are performed on a MATLAB R2012a platform. The experimental results show that our spatial-temporal visual attention model demonstrates favorable robustness under various scenes, including indoor train station surveillance videos and outdoor scenes with swaying leaves. Our proposed model outperforms the visual attention model of Itti, the graph-based visual saliency model, the phase spectrum of quaternion Fourier transform model, and the motion channel model of Liu in terms of pedestrian detection. The proposed model achieves a 93% accuracy rate on the test video.
Conclusion
This paper proposes a novel pedestrian method based on the visual attention mechanism. A spatial-temporal visual attention model that uses low-level and semantic features is proposed to calculate the saliency map. Based on this model, the pedestrian targets can be detected through focus of attention shifts. The experimental results verify the effectiveness of the proposed attention model for detecting pedestrians.

Powers, liabilities and expertise in community safety: Comparative lessons for ‘urban security’ from the United Kingdom and the Republic of Ireland

This paper begins by outlining and critiquing what we term the dominant anglophone model of neo-liberal community safety and crime prevention. As an alternative to this influential but flawed model, a comparative analysis is provided of the different constitutional-legal settlements in each of the five jurisdictions across the UK and the Republic of Ireland (ROI), and their uneven institutionalization of community safety. In the light of this it is argued that the nature of the anglophone community safety enterprise is actually subject to significant variation. Summarizing the contours of this variation facilitates our articulation of some core dimensions of community safety. Then, making use of Colebatch’s (2002) deconstruction of policy activity into categories of authority and expertise, and Brunsson’s (2002) distinction between policy talk, decisions and action, we put forward a way of understanding policy activity that avoids the twin dangers of ‘false particularism’ and ‘false universalism’ (Edwards and Hughes, 2005); that indicates a path for further empirical enquiry to assess the ‘reality’ of policy convergence; and that enables the engagement of researchers with normative questions about where community safety should be heading.

Comparison of excess radiological risk of building materials and industrial by-products according to I-index (EU-BSS) and revised room model (IAEA SSG-32)

To get a better insight into the radiological features of industrial by-products that can be reused in building materials a review of the reported scientific data can be very useful. The current study is based on the continuously growing database of the By-BM (H2020-MSCA-IF-2015) project (By-products for Building Materials). Currently, the By-BM database contains individual data of about 431 by-products and 1095 building and raw materials. It was found that in case of the building materials the natural radionuclide content varied widely (Ra-226: <DL-27851 Bq/kg; Th-232: <DL-906 Bq/kg, K-40: <DL-17922 Bq/kg), more so than for the by-products (Ra-226: 7-3152 Bq/kg; Th-232: <DL-1350 Bq/kg, K-40: <DL-3001 Bq/kg). The average Ra-226, Th-232 and K-40 contents of the reported by-products were respectively 2.52, 2.35 and 0.39 times higher than the building materials. The gamma exposure of bulk building products was calculated according to IAEA Specific Safety Guide No. SSG-32 and the European Commission Radiation Protection 112 based I-index (EU BSS). It was found that in most cases the I-index without density consideration provides a significant overestimation in excess effective dose.

A Combined Molecular Cloning and Mass Spectrometric Method to Identify, Characterize, and Design Frenatin Peptides from the Skin Secretion of Litoria infrafrenata

Amphibian skin secretions are unique sources of bioactive molecules, particularly bioactive peptides. In this study, the skin secretion of the white-lipped tree frog (Litoria infrafrenata) was obtained to identify peptides with putative therapeutic potential. By utilizing skin secretion-derived mRNA, a cDNA library was constructed, a frenatin gene was cloned and its encoded peptides were deduced and confirmed using RP-HPLC, MALDI-TOF and MS/MS. The deduced peptides were identified as frenatin 4.1 (GFLEKLKTGAKDFASAFVNSIKGT) and a post-translationally modified peptide, frenatin 4.2 (GFLEKLKTGAKDFASAFVNSIK.NH2). Antimicrobial activity of the peptides was assessed by determining their minimal inhibitory concentrations (MICs) using standard model microorganisms. Through studying structure–activity relationships, analogues of the two peptides were designed, resulting in synthesis of frenatin 4.1a (GFLEKLKKGAKDFASALVNSIKGT) and frenatin 4.2a (GFLLKLKLGAKLFASAFVNSIK.NH2). Both analogues exhibited improved antimicrobial activities, especially frenatin 4.2a, which displayed significant enhancement of broad spectrum antimicrobial efficiency. The peptide modifications applied in this study, may provide new ideas for the generation of leads for the design of antimicrobial peptides with therapeutic applications.