Understanding dynamic scenes based on human sequence evaluation

In this paper, a Cognitive Vision System (CVS) is presented, which explains the human behaviour of monitored scenes using naturallanguage texts. This cognitive analysis of human movements recorded in image sequences is here referred to as Human Sequence Evaluation (HSE) which defines a set of transf...

Descripción completa

Detalles Bibliográficos
Autores: González Sabaté, Jordi, Rowe, Daniel, Varona, Javier, Roca, Francesc Xavier
Tipo de recurso: artículo
Fecha de publicación:2009
País:España
Institución:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2117/6501
Acceso en línea:https://hdl.handle.net/2117/6501
https://dx.doi.org/10.1016/j.imavis.2008.02.004
Access Level:acceso abierto
Palabra clave:Cognitive technologies
Artificial vision
Visió artificial (Robòtica)
Cognició -- Investigació
Àrees temàtiques de la UPC::Informàtica::Robòtica
Descripción
Sumario:In this paper, a Cognitive Vision System (CVS) is presented, which explains the human behaviour of monitored scenes using naturallanguage texts. This cognitive analysis of human movements recorded in image sequences is here referred to as Human Sequence Evaluation (HSE) which defines a set of transformation modules involved in the automatic generation of semantic descriptions from pixel values. In essence, the trajectories of human agents are obtained to generate textual interpretations of their motion, and also to infer the conceptual relationships of each agent w.r.t. its environment. For this purpose, a human behaviour model based on Situation Graph Trees (SGTs) is considered, which permits both bottom-up (hypothesis generation) and top-down (hypothesis refinement) analysis of dynamic scenes. The resulting system prototype interprets different kinds of behaviour and reports textual descriptions in multiple languages.