Mobile objects and sensors within a video surveillance system: Spatio-temporal model and queries

International audienceThe videos recorded by video surveillance systems represent a key element in a police inquiry. Based on a spatio-temporal query specified by a victim, (e.g., the trajectory of the victim before and after the aggression) the human operators select the cameras that could contain relevant information and analyse the corresponding video contents. This task becomes cumbersome because of the huge volume of video contents and the cameras' mobility. This paper presents an approach, which assists the operator in his task and reduces the research space. We propose to model the cameras' network (fixed and mobile cameras) on top of the city's transportation network. We consider the video surveillance system as a multilayer geographic information system, where the cameras are situated into a distinct layer, which is added on top of the other layers (e.g., roads, transport) and is related to them by the location. The model is implemented in a spatio-temporal database. Our final goal is that based on a spatio-temporal query to automatically extract the list of cameras (fixed and mobile) concerned by the query. We propose to include this automatically computed relative position of the cameras as an extension of the standard ISO 22311

Spatial Search Strategies for Open Government Data: A Systematic Comparison

The increasing availability of open government datasets on the Web calls for ways to enable their efficient access and searching. There is however an overall lack of understanding regarding spatial search strategies which would perform best in this context. To address this gap, this work has assessed the impact of different spatial search strategies on performance and user relevance judgment. We harvested machine-readable spatial datasets and their metadata from three English-based open government data portals, performed metadata enhancement, developed a prototype and performed both a theoretical and user-based evaluation. The results highlight that (i) switching between area of overlap and Hausdorff distance for spatial similarity computation does not have any substantial impact on performance; and (ii) the use of Hausdorff distance induces slightly better user relevance ratings than the use of area of overlap. The data collected and the insights gleaned may serve as a baseline against which future work can compare.Comment: Paper accepted to GIR'19: 13th Workshop on Geographic Information Retrieval (Lyon, France

Relevance Criteria when Searching and Evaluating Online Video for Informational Use

Relevance is a core concept in the field of Information Science and a common term in everyday vernacular that generally refers to the usefulness of information. However, relevance has not been sufficiently or consistently defined or explored in the information science literature. Relevance criteria are the factors that information users employ when determining whether information they encounter is relevant. Identifying relevance criteria is a crucial step to understanding relevance. Relevance criteria employed with newer information formats like online video are especially important to study. Online video is now widespread, and people are increasingly likely to rely on video for information. This study identifies relevance criteria employed during relevance assessments of online video through a explanatory sequential mixed-methods study of frequent online video users including students, faculty, librarians, and video professionals. Methods included an online survey and interviews

Relevance ranking in georeferenced video search

10.1007/s00530-009-0177-xMultimedia Systems162105-125MUSY