An osmotic imbalance between the two water phases of multiple water-in-oil-in-water (W1/O/W2) emulsions results in either emulsion swelling or shrinking due to water migration across the oil layer. Controlled mass transport is not only of importance for emulsion stability but also allows transient emulsion thickening or the controlled release of encapsulated substances, such as nutriments or simply salt. Our prior work has shown that mass transport follows two sequential stages. In the first stage, the oil-phase structure is changed in a way that allows rapid, osmotically driven water transport in the second, osmotically dominated stage. These structural changes in the oil layer are strongly facilitated by the spontaneous formation of tiny water droplets in the oil phase, induced by the oil-soluble surfactant, i.e., polyglycerol polyricinoleate (PGPR). This study provides a simple method based on microscopy image analysis, allowing a detailed investigation of spontaneous W/O emulsification. It quantitatively describes the volume of droplets generated and the rate of droplet creation. Moreover, it describes the effect of spontaneous W/O emulsification on the swelling kinetics of microfluidic processed W1/O/W2 emulsions. Two different concentration regimes of the oil-soluble surfactant are identified: below a critical concentration the overall water transport rate increases, and above a critical concentration water transport stagnates because of maximized structure formation.

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In this paper, we investigate on the feasibility of multiple camera system for automatic offside detection. We propose six fixed cameras, properly placed on the two sides of the soccer field (three for each side) to reduce perspective and occlusion errors. The images acquired by the synchronized cameras are processed to detect the players' position and the ball position in real-time; a multiple view analysis is carried out to evaluate the offside event, considering the position of all the players in the field, determining the players who passed the ball, and determining if active offside condition occurred. The whole system has been validated using real-time images acquired during official soccer matches, and quantitative results on the system accuracy were obtained comparing the system responses with the ground truth data generated manually on a number of extracted significant sequences. Index Terms-3-D trajectory analysis, multiple cameras, player and ball tracking.

In this paper we tackle the problem of indoor robot localization by using a vision-based approach. Specifically, we propose a visual odometer able to give back the relative pose of an omnidirectional automatic guided vehicle (AGV) that moves inside an indoor industrial environment. A monocular downward-looking camera having the optical axis nearly perpendicular to the ground floor, is used for collecting floor images. After a preliminary analysis of images aimed at detecting robust point features (keypoints) takes place, specific descriptors associated to the keypoints enable to match the detected points to their consecutive frames. A robust correspondence feature filter based on statistical and geometrical information is devised for rejecting those incorrect matchings, thus delivering better pose estimations. A camera pose compensation is further introduced for ensuring better positioning accuracy. The effectiveness of proposed methodology has been proven through several experiments, in laboratory as well as in an industrial setting. Both quantitative and qualitative evaluations have been made. Outcomes have shown that the method provides a final positioning percentage error of 0.21% on an average distance of 17.2 m. A longer run in an industrial context has provided comparable results (a percentage error of 0.94% after about 80 m). The average relative positioning error is about 3%, which is still in good agreement with current state of the art.

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In the last decade, several research efforts have been undertaken in soccer video analysis. This increasing interest is motivated by the possible applications over a wide spectrum of topics: indexing, summarization, video enhancement, team and players statistics, tactic analysis, referee's support, etc. Soccer video analysis requires different challenging tasks: ball and players have to be localized in each frame, tracked over time and, above all, their interactions have to be detected and analyzed. The latter task is fundamental, especially for statistics and referee decision support purposes, but, unfortunately, it has not received adequate attention from the scientific community. In this paper a multi-view system able to understand in real time the interactions between the ball and the players is presented. 3D ball trajectories are extracted by triangulation from multiple cameras and used to detect the interactions between the players and the ball. Inference processes are then introduced to determine the player kicking the ball and to fix the instant of the interaction. The system has been tested during several matches of the Italian first division soccer championship and experimental proofs of its effectiveness are reported.

In response to prevailing classification inconsistency between land cover maps, developed by different organizations in different times at different scales, an object-based National Land Representation System (NLRS) for Bangladesh has been developed. The process, which began in 2013 and was completed in 2016, brought together several national organizations and involved an extensive process of consultation, data collection, translation, and analysis of existing land cover/use classification systems. The process focused on the interpretation of three legends from historic national land cover/use maps. Field inventory data were collected from over 1000 sites across the country to assist the process of land characterization and the development of a dynamic and representative overview of land cover and land use in Bangladesh. The system has been applied to the development of a wall-to-wall national land cover map for the year 2015. In this article, the methodological process and results of NLRS formulation and land cover map 2015 are presented. We also provide examples of how this interoperable system and the land cover dataset are being used for variety of applications including national forest resources assessment, estimation of REDD+ activity data, integration of biophysical and socioeconomic information, and semantic similarity assessment.