On the way of integrating evacuation approaches

With the growing pressure on available urban space and the construction of more and more complex building infrastructures, the navigational task for building users is getting increasingly difficult. As people react more impulsive under stressful situations, emergencies can exacerbate way finding problems. Additionally, leadership and familiarity with the (topological structure of a) building can influence the ease of finding appropriate evacuation routes. In research, two separate and distinctive techniques for modelling evacuation paths have been developed: evacuation simulation modelling through complex computer simulations and 3D network modelling based on graph theory. Taking into account a global user perspective, the 3D network modelling approach has the advantage to preserve a close connection with the semantic building structure. Following this approach, existing three dimensional evacuation routing algorithms tend to use Dijkstra's shortest path algorithm. However, as more factors, compared to path length, influence evacuation situations, literature acknowledges a void in representing more realistic, complete and accurate emergency situations. This paper presents a first step in creating such integral algorithm by implementing capacity constraints based on user flow control on a 3D geometric network model. In the future additional topics such as zonal partitioning can be added to the algorithm, moving to an integration of both evacuation approaches

Unsupervised Methods for Camera Pose Estimation and People Counting in Crowded Scenes

Most visual crowd counting methods rely on training with labeled data to learn a mapping between features in the image and the number of people in the scene. However, the exact nature of this mapping may change as a function of different scene and viewing conditions, limiting the ability of such supervised systems to generalize to novel conditions, and thus preventing broad deployment. Here I propose an alternative, unsupervised strategy anchored on a 3D simulation that automatically learns how groups of people appear in the image and adapts to the signal processing parameters of the current viewing scenario. To implement this 3D strategy, knowledge of the camera parameters is required. Most methods for automatic camera calibration make assumptions about regularities in scene structure or motion patterns, which do not always apply. I propose a novel motion based approach for recovering camera tilt that does not require tracking. Having an automatic camera calibration method allows for the implementation of an accurate crowd counting algorithm that reasons in 3D. The system is evaluated on various datasets and compared against state-of-art methods

A Review of Hybrid Indoor Positioning Systems Employing WLAN Fingerprinting and Image Processing

Location-based services (LBS) are a significant permissive technology. One of the main components in indoor LBS is the indoor positioning system (IPS). IPS utilizes many existing technologies such as radio frequency, images, acoustic signals, as well as magnetic sensors, thermal sensors, optical sensors, and other sensors that are usually installed in a mobile device. The radio frequency technologies used in IPS are WLAN, Bluetooth, Zig Bee, RFID, frequency modulation, and ultra-wideband. This paper explores studies that have combined WLAN fingerprinting and image processing to build an IPS. The studies on combined WLAN fingerprinting and image processing techniques are divided based on the methods used. The first part explains the studies that have used WLAN fingerprinting to support image positioning. The second part examines works that have used image processing to support WLAN fingerprinting positioning. Then, image processing and WLAN fingerprinting are used in combination to build IPS in the third part. A new concept is proposed at the end for the future development of indoor positioning models based on WLAN fingerprinting and supported by image processing to solve the effect of people presence around users and the user orientation problem

Human Motion Trajectory Prediction: A Survey

With growing numbers of intelligent autonomous systems in human environments, the ability of such systems to perceive, understand and anticipate human behavior becomes increasingly important. Specifically, predicting future positions of dynamic agents and planning considering such predictions are key tasks for self-driving vehicles, service robots and advanced surveillance systems. This paper provides a survey of human motion trajectory prediction. We review, analyze and structure a large selection of work from different communities and propose a taxonomy that categorizes existing methods based on the motion modeling approach and level of contextual information used. We provide an overview of the existing datasets and performance metrics. We discuss limitations of the state of the art and outline directions for further research.Comment: Submitted to the International Journal of Robotics Research (IJRR), 37 page

MULTI-SENSOR LOCALIZATION AND TRACKING IN DISASTER MANAGEMENT AND INDOOR WAYFINDING FOR VISUALLY IMPAIRED USERS

This dissertation proposes a series of multi-sensor localization and tracking algorithms particularly developed for two important application domains, which are disaster management and indoor wayfinding for blind and visually impaired (BVI) users. For disaster management, we developed two different localization algorithms, one each for Radio Frequency Identification (RFID) and Bluetooth Low Energy (BLE) technology, which enable the disaster management system to track patients in real-time. Both algorithms work in the absence of any pre-deployed infrastructure along with smartphones and wearable devices. Regarding indoor wayfinding for BVI users, we have explored several types of indoor positioning techniques including BLE-based, inertial, visual and hybrid approaches to offer accurate and reliable location and orientation in complex navigation spaces. In this dissertation, significant contributions have been made in the design and implementation of various localization and tracking algorithms under different requirements of certain applications