This paper proposes a model-based methodology for recognizing and tracking objects in digital image sequences. Objects are represented by attributed relational graphs (or ARGs), w...
Ana Beatriz V. Graciano, Roberto Marcondes Cesar J...
In artificial intelligence and pervasive computing research, inferring users' high-level goals from activity sequences is an important task. A major challenge in goal recogni...
In this paper we present a novel approach using a 4D (x,y,z,t) action feature model (4D-AFM) for recognizing actions from arbitrary views. The 4D-AFM elegantly encodes shape and m...
Activity recognition is a key component for creating intelligent, multi-agent systems. Intrinsically, activity recognition is a temporal classification problem. In this paper, we...
Douglas L. Vail, Manuela M. Veloso, John D. Laffer...
Abstract This paper focuses on human behavior recognition where the main problem is to bridge the semantic gap between the analogue observations of the real world and the symbolic ...