As technology advances we encounter more available data on moving objects, which can be mined to our benefit. In order to efficiently mine this large amount of data we propose an ...
In this paper a framework “Temporal-Vector Trajectory Learning” (TVTL) for human action recognition is proposed. In this framework, the major concept is that we would like to a...
Human behavior recognition is one of the most important and challenging objectives performed by intelligent vision systems. Several issues must be faced in this domain ranging fro...
We present a new representation and recognition method for human activities. An activity is considered to be composed of action threads, each thread being executed by a single act...
We propose a framework for general multiple target tracking, where the input is a set of candidate regions in each frame, as obtained from a state of the art background learning, ...