Emanuele Frontoni

Shopper Analytics: a customer activity recognition system using a distributed RGB-D camera network

The aim of this paper is to present an integrated system consisted of a RGB-D camera and a software able to monitor shoppers in intelligent retail environments. We propose an innovative low cost smart system that can understand the shoppers’ behavior and, in particular, their interactions with the products in the shelves, with the aim to develop an automatic RGB-D technique for video analysis. The system of cameras detects the presence of people and univocally identifies them. Through the depth frames, the system detects the interactions of the shoppers with the products on the shelf and determines if a product is picked up or if the product is taken and then put back and finally, if there is not contact with the products. The system is low cost and easy to install, and experimental results demonstrated that its performances are satisfactory also in real environments.

Low cost embedded system for increasing retail environment intelligence

The success of pervasive smart environments lies in the capacity to involve visitors to interact with them. It is essential for retail stores. In this paper we describe the setting-up of a low cost system for the indoor localization and customer interaction, developed with a complex infrastructure of wireless embedded sensors. The creation of a responsive store allows customers to connect the real world to their smart devices and will overcome the lack of ubiquity in public spaces; furthermore, from in-venue analytics and proximity sensor it is possible to customize the user experience. First of all we describe the whole sensor network. We go in deep into the active beacon technology adopted for this study. Then, thanks to the analytics, we present a data evaluation with the aim of determining the best sensor arrangement, according to several user tests. Beside the strong enhancement of human interaction, the results of our essay demonstrate how embedded localization systems could be a useful source for data collection beside the strong enhancement of human interaction. This paper is focused to help retailers and insiders for many purposes such as products development or improvement, segmentation strategies and human behaviour analyses into such stores where the embedded computing augment the environment.

Interoperability issues among smart home technological frameworks

Population aging may be seen both as a human success story, the triumph of public health, medical advancements and economic development over diseases and injures, and as one of the most challenging phenomena that society faces in this century. Assistive technology in all its possible implementations (from Telemedicine to Ambient Assisted Living, and Ambient Intelligence) represents an emerging answer to the needs of the new generation of older adults whose desire is to live longer with a higher quality of life. Objective of this paper is to present the results of a public financed action for the development and implementation of an “integration platform” for Ambient Assisted Living that includes features of home automation (energy management, safety, comfort, etc.) and introduces “smart objects”, to monitor activities of daily living and detect any abnormal behavior that may represent a danger, or highlight symptoms of some incipient disease.

Making Visible the Invisible. Augmented Reality Visualization for 3D Reconstructions of Archaeological Sites

In archaeology, findings are completely freed from the earth which had been covering for centuries but in most cases they must be covered again in order to protect them. In this paper we present a augmented reality AR experience for the visualization of 3D models in-situ, giving the possibility to see conceived findings. The experience was carried out for archaeological purposes in Chan Chan, the Americas greatest pre-Columbian town. From 2001, our mission is operating at Chan Chan carrying on a wide action of documentation, conservation and exploitation. We propose an interesting workflow: image acquisition, 3D photogrammetric reconstruction, 3D simplification, AR visualization. Also a knowledge base applied to archaeological sites is here presented.

Advanced Interaction with Paintings by Augmented Reality and High Resolution Visualization: A Real Case Exhibition

In this paper, an interactive installation system for the enjoyment of the cultural heritage in a real case museum environment is presented. By using Augmented Reality technology, mobile application and High Resolution visualization we provide the users with a visual augmentation of their surroundings and a touch interaction technique to display digital contents for cultural heritage promotion, allowing museum visitors to interact with digital contents in an intuitive and exciting manner. The exhibition here presented is the result of previous research over the use of new technologies e.g. Augmented Reality for Cultural Heritage promotion. Descriptions of the hardware system component and software development details are presented, with particular focus over the application implementation. Furthermore, we outline a possible Multimedia AR Installation connected with a semantic network.

Unmanned Ground and Aerial Vehicles in extended range indoor and outdoor missions

The capability to instantiate a cooperation among heterogeneous agents is a fundamental feature in mobile robotics. In this paper we focus on the interaction between Unmanned Ground Vehicle (UGV) and Unmanned Aerial Vehicle (UAV) to extend the endurance of UAV, thanks to a novel landing/recharging platform. The UGV acts as a docking station and hosts the UAV during the indoor/outdoor transition and vice-versa. We designed a platform and a robust landing target to automate the fast recharge of UAV. The synchronization and coordination of cooperation is managed by a Ground Control Station (GCS) developed using a versatile software toolchain based on the integration of Stateflow, auto-generation of C-code and ROS. All the software components of UAV, UGV and GCS have been developed using ROS. The obtained results show that the UAV is able to land over the UGV with high accuracy (<;5cm for both x and y axis) thanks to a visual position estimation algorithm, also in presence of wind (with gust up to 20-25km/h), recharging its batteries in a short time to extend its endurance.

Embedded Vision Sensor Network for Planogram Maintenance in Retail Environments

A planogram is a detailed visual map that establishes the position of the products in a retail store. It is designed to supply the best location of a product for suppliers to support an innovative merchandising approach, to increase sales and profits and to better manage the shelves. Deviating from the planogram defeats the purpose of any of these goals, and maintaining the integrity of the planogram becomes a fundamental aspect in retail operations. We propose an embedded system, mainly based on a smart camera, able to detect and to investigate the most important parameters in a retail store by identifying the differences with respect to an “approved” planogram. We propose a new solution that allows concentrating all the surveys and the useful measures on a limited number of devices in communication among them. These devices are simple, low cost and ready for immediate installation, providing an affordable and scalable solution to the problem of planogram maintenance. Moreover, over an Internet of Things (IoT) cloud-based architecture, the system supplies many additional data that are not concerning the planogram, e.g., out-of-shelf events, promptly notified through SMS and/or mail. The application of this project allows the realization of highly integrated systems, which are economical, complete and easy to use for a large number of users. Experimental results have proven that the system can efficiently calculate the deviation from a normal situation by comparing the base planogram image with the images grabbed.

High-resolution mapping of river and estuary areas by using unmanned aerial and surface platforms

The accurate and precise mapping of Land Use / Land Cover (LU/LC) plays a key role in the management of a region. In particular the knowledge of areas close to rivers and / or estuaries is fundamental to prevent flooding preserving the integrity of artificial structures and natural flora and fauna. Actually the mapping is performed by processing remote sensed data with a typical GSD of 0.5m. The survey is expensive and the presence of clouds could invalidate an entire survey. This kind of survey is perfect for a monitoring over a long period while is not appropriate for a quasi real time imagery. The adoption of unmanned aerial vehicles (UAVs) is a proper solution owing to the low cost and the reduced time for the setup, but it lacks of a complete view of the area. The reason is the presence of canopy that occludes the view. We integrate the images acquired by an UAV characterized by a GSD of 0.03m with an Unmanned Surface Vehicle (USV) that collects images of the river from different point of view enhanced by an RGB-D sensor. The change detection algorithm applied to the collected data is based on a innovative hybrid classifier that fuses the benefit of pixel and object based approaches mapping the changes over a well defined temporal horizon.

Human activity analysis for in-home fall risk assessment

The aim of this work is to define a fall detection video system for indoor environments based on a RGB-D sensor and a low power and low cost embedded system that processes the sensor data in order to provide a description of human activities in the field of the Ambient Assisted Living. The RGB image is affected by a high luminescence sensibility, so the depth data have the aim to improve the human activity recognition. The system is usable in a sufficiently small room and it requires a RGB-D sensor located in the center of the ceiling and an embedded system connected on a computer network. The embedded system controls the RGB-D sensor and, in the mean time, classifies the images using computer vision algorithms based on the depth map. “Water Filling” algorithm or “Multi-Level Segmentation” algorithm are used to detect person. For each person, the system detects the position with respect to the room, estimating also the human posture. Among the features extracted we enumerate the height, the head size and the distance between the head and the shoulders. The system tracks a person through the frames starting from the first identification. Further, group interactions are monitored and analyzed. The posture detection algorithm takes into account the distance between the person head and the floor during the time. During the experimental phase, conducted in many domestic scenarios, the effectiveness of the proposed solution has been proved, that is fast, accurate and ables to provide a fall map in-home fall risk assessment.

Shelf space re-allocation for out of stock reduction

An ILP formulation is proposed for Shelf space re-allocation problem.Out-of-stock data are collected from the Shelf Detector System in real time.Space elastic demand function is linked with real-time statistical data.Tests performed on real, random and large instances. A planogram is a detailed visual map that establishes product positions over a shelf in a retail store. It is designed to support an innovative merchandising approach, to increase sales and profits, to supply the best location of a product for suppliers and to better manage the shelves. Product selection and the shelf space reserved to each product is a central activity for retailers and Shelf Out of Stock (SOOS) events are often strongly related to planogram design. In this paper we present a solution to optimally re-allocate shelf space to minimize Out of Stock (OOS) events. The approach uses SOOS data coming in real time from a sensor network technology, named Shelf Detector System, and an Integer Linear Programming model that integrates a space elastic demand function. Experimental results, based on a real scenario in the diaper category in Belgium, have proved that the system can efficiently calculate a proper solution able to re-allocate space and reduce OOS events.