Visual Crowd Analysis: Open Research Problems

Over the last decade, there has been a remarkable surge in interest in automated crowd monitoring within the computer vision community. Modern deep-learning approaches have made it possible to develop fully-automated vision-based crowd-monitoring applications. However, despite the magnitude of the issue at hand, the significant technological advancements, and the consistent interest of the research community, there are still numerous challenges that need to be overcome. In this article, we delve into six major areas of visual crowd analysis, emphasizing the key developments in each of these areas. We outline the crucial unresolved issues that must be tackled in future works, in order to ensure that the field of automated crowd monitoring continues to progress and thrive. Several surveys related to this topic have been conducted in the past. Nonetheless, this article thoroughly examines and presents a more intuitive categorization of works, while also depicting the latest breakthroughs within the field, incorporating more recent studies carried out within the last few years in a concise manner. By carefully choosing prominent works with significant contributions in terms of novelty or performance gains, this paper presents a more comprehensive exposition of advancements in the current state-of-the-art.Comment: Accepted in AI Magazine published by Wiley Periodicals LLC on behalf of the Association for the Advancement of Artificial Intelligenc

Validation and evaluation of NEMO in VANET using geographic routing

International audienceThe combination of geographic-based routing protocols (GeoNetworking) and IPv6 NEtwork MObility (NEMO) into a single communication architecture (IPv6 GeoNetworking) is key in Vehicular Ad-hoc Networks (VANET). While NEMO manages Internet access and session continuity between the vehicle and the Internet, geographically based data forwarding allows an efficient dissemination of the information between vehicles and the infrastructure. In this paper, we refer to the basic scenarios that led to the design of the IPv6 GeoNetworking architecture in the context of the GeoNet project. A prototype implementation of the modules that couple these two technologies is described, in particular the adaptation of IPv6 and C2CNet, a layer that ensures the geographic capabilities. Results of a light experimental performance evaluation are reported

Experimental Evaluation for IPv6 over VANET Geographic routing

International audienceVehicular communication is an important part of the Intelligent Transportation Systems (ITS). Geographic routing in vehicular ad hoc network (VANET) is becoming an interesting topic to deliver safety messages between cars but also between a car and a roadside infrastructure within a designated destination area. The Car2Car Communication Consortium specified C2CNet architecture as a geographic routing protocol. The results of GeoNet project are presented in the paper, which aims at combining IPv6 networking and C2CNet. The system with IPv6 and C2CNet is designed and implemented in Linux. The prototype implementation is first evaluated indoor testbed with the fixed positions. Then it is evaluated in the field testbed with three vehicles with various scenarios. For evaluation in field testbed, we have developed the AnaVANET evaluation tool to perform the evaluation taking into account all of geographic factors