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4 May 2009 Motion detection with camera shake
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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, and Shun'ichi Kaneko "Motion detection with camera shake", Proc. SPIE 7338, Acquisition, Tracking, Pointing, and Laser Systems Technologies XXIII, 73380E (4 May 2009);


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