Recognition of human and animal movement using infrared video streams (TA-L3)

Author(s) : Qin Jiang (HRL Laboratories, LLC, USA) Cindy Daniell (HRL Laboratories, LLC, USA)

Abstract : Distinguishing human motion from animal motion is important in many applications using infrared video streams, such as surveillance systems for homeland security and collision avoidance systems for nighttime driving safety. In this paper, we present a technique to distinguish human motion from animal motion using infrared video sequences. In our technique, we use frame difference to represent object motion. Correlations computed in 3D space are used to characterize different type of motions. Our motion features are defined by Renyi entropy and mean values calculated from the correlations. A support vector machine-based classifier is used to classify the motion features. Our experimental results show that our technique is quite effective to distinguish human motion from animal motion using infrared video sequences.

Menu