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1. Introduction
Over the last few decades, human activity analysis has undergone rapid development receiving increasing attention in many fields, such as intelligent surveillance, human-computer interaction, and elder care management [1, 2]. Human activity can be categorized according to complexity as partial body action [3], simple action [4], interaction activity [5, 6], or group activity [7]. Motivated by the activity classes drawn from [5, 6], this paper focuses on two-person interaction recognition of six complex interactions: kicking, pointing, pushing, punching, exchanging an object, and shaking hands.
Much research has been done on two-person interactions [5–10] with respect to the kinds of complex action relationships and human features necessary for recognition. For example, [5] took into account whether one person’s hand is above another’s shoulder or whether one person’s foot is near another’s torso. Reference [6] used head-pose, arm-pose, leg-pose, and overall body-pose estimation with both people for recognition. However, these processes are complex and time consuming and the recognition results might not be as accurate as required for a particular application. This paper proposes a new definition for interactions based on one person’s behavior called Positive Action. In this method, one person’s action plays the key role in an interaction; thus, two-person interaction recognition can be simplified into Positive Action recognition. This approach is simpler than traditional methods, saves computing time, and improves recognition results.
The recent proliferation of a cheap but effective depth sensor, the Microsoft Kinect [11], has created more opportunities for quantitative analysis of complex human activities. As compared to the traditional video camera, Kinect has the advantage of synchronous acquisition of color and depth images; with the use of depth maps, 3D information about a scene from a particular point of view...