Attention-from-motion: A factorization approach for detecting attention objects in motion

  • Authors:

  • Yiqun Hu;Deepu Rajan;Liang-Tien Chia

  • Affiliations:

  • School of Computer Engineering, Nanyang Technological University, Nanyang Avenue, Singapore 639798, Singapore;School of Computer Engineering, Nanyang Technological University, Nanyang Avenue, Singapore 639798, Singapore;School of Computer Engineering, Nanyang Technological University, Nanyang Avenue, Singapore 639798, Singapore

  • Venue:
  • Computer Vision and Image Understanding
  • Year:
  • 2009

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Abstract

This paper introduces the notion of attention-from-motion in which the objective is to identify, from an image sequence, only those object in motions that capture visual attention (VA). Following the important concept in film production, viz, the tracking shot, we define the attention object in motion (AOM) as those that are tracked by the camera. Three components are proposed to form an attention-from-motion framework: (i) a new factorization form of the measurement matrix to describe dynamic geometry of moving object observed by moving camera; (ii) determination of single AOM based on the analysis of certain structure on the motion matrix; (iii) an iterative framework for detecting multiple AOMs. The proposed analysis of structure from factorization enables the detection of AOMs even when only partial data is available due to occlusion and over-segmentation. Without recovering the motion of either object or camera, the proposed method can detect AOM robustly from any combination of camera motion and object motion and even for degenerate motion.