Event Understanding of Human-Object Interaction: Object Movement Detection via Stable Changes - Intelligent Video Event Analysis and Understanding - page 195

Event Understanding of Human-Object
Interaction: Object Movement Detection via
Stable Changes

Shigeyuki Odashima, Taketoshi Mori, Masamichi Simosaka,
Hiroshi Noguchi, and Tomomasa Sato

Abstract. This chapter proposes an object movement detection method in house-
hold environments. The proposed method detects “object placement” and “object
removal” via images captured by environment-embedded cameras. When object
movement detection is performed in household environments, there are several dif-
ficulties: the method needs to detect object movements robustly even if sizes of
objects are small, the method must discriminate objects and non-objects such as hu-
mans. In this work, we propose an object movement detection method by detecting
“stable changes”, which are changing from the recorded state but which change are
settled. To categorize objects and non-objects via the stable changes even though
non-objects make long-term changes (e.g. a person is sitting down), we employ mo-
tion history of changed regions. In addition, to classify object placement and object
removal, we use multiple-layered background model, called the layered background
model and edge subtraction technique. The experiment shows the system can detect
objects robustly and in sufficient frame-rates.

1 Introduction

Recently, recording daily activities as a lifelog has become feasible due to the
wide-spread use of digital cameras and large-scale computer storages. As shown in
Fig. 1, object tracking systems that focus on object placement and removal events in
lifelogs are possible by using environment-embedded cameras. The object tracking