Fall detection using directional bounding box
Apichet Yajai, Annupan Rodtook, Krisana Chinnasarn, Suwanna Rasmequan · 2015
Falls are significant public health problem. In the last few years, several researches based on computer vision system have been developed to detect a person who has fallen to the ground. This paper presents a novel fall detection technique namely the directional bounding box (DBB) to detect a falls event especially a situation of fall direction paralleling the line of camera's sight. The DBB is constructed with perspective side view transformation of depth information. Moreover, a new aspect ratio namely the center of gravity point (COG) is proposed to monitor human movement. The proposed technique was evaluated with the video data set gathering from a RGB-D sensor. The experimental result of the proposed technique was better both accuracy and response times than previous works.