4 May 2009 Motion detection with camera shake
Author Affiliations +
Abstract
A method for detecting an object's motion in images that suffer from camera shake or images with camera egomotion is proposed. This approach is based on edge orientation codes and on the entropy calculated from a histogram of the edge orientation codes. Here, entropy is extended to spatio-temporal entropy. We consider that the spatio-temporal entropy calculated from time-series orientation codes can represent motion complexity, e.g., the motion of a pedestrian. Our method can reject false positives caused by camera shake or background motion. Before the motion filtering, object candidates are detected by a frame-subtraction-based method. After the filtering, over-detected candidates are evaluated using the spatio-temporal entropy, and false positives are then rejected by a threshold. This method could reject 79 to 96 [%] of all false positives in road roller and escalator scenes. The motion filtering decreased the detection rate somewhat because of motion coherency or small apparent motion of a target. In such cases, we need to introduce a tracking method such as Particle Filter or Mean Shift Tracker. The running speed of our method is 32 to 46 ms per frame with a 160×120 pixel image on an Intel Pentium 4 CPU at 2.8 GHz. We think that this is fast enough for real-time detection. In addition, our method can be used as pre-processing for classifiers based on support vector machines or Boosting.
© (2009) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Masato Kazui, Masaya Itoh, Hiroki Yaemori, Hidenori Takauji, Shun'ichi Kaneko, "Motion detection with camera shake", Proc. SPIE 7338, Acquisition, Tracking, Pointing, and Laser Systems Technologies XXIII, 73380E (4 May 2009); doi: 10.1117/12.818749; https://doi.org/10.1117/12.818749
PROCEEDINGS
9 PAGES


SHARE
RELATED CONTENT

Accurate generation of the 3D map of environment with a...
Proceedings of SPIE (September 19 2017)
Dynamic workspace monitoring
Proceedings of SPIE (August 17 1994)
Novel algorithm of road vehicles detection
Proceedings of SPIE (September 24 2001)
Using multispectral information for 3D reconstruction
Proceedings of SPIE (February 24 2005)
Feature selection for object tracking in traffic scenes
Proceedings of SPIE (January 06 1995)

Back to Top