Detection of moving foreground objects in videos with strong camera motion

Szolgay, Dániel; Benois-Pineau, Jenny; Megret, Rémi; Gaëstel, Yann; Dartigues, Jean François

doi:10.1007/s10044-011-0221-2

Cited by 19 publications

(14 citation statements)

References 23 publications

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“…The context of actual work is the multi-disciplinary research on Alzheimer disease [11,12]. The goal here is to ensure an objective assessment of the capacity of patients to conduct the IADL (Instrumental Activities of Daily Living).…”

Section: Motivationsmentioning

confidence: 99%

Fusion of Multiple Visual Cues for Visual Saliency Extraction from Wearable Camera Settings with Strong Motion

Boujut

Benois-Pineau

Megret

2012

Computer Vision – ECCV 2012. Workshops and Demonstrations

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Abstract. In this paper we are interested in the saliency of visual content from wearable cameras. The subjective saliency in wearable video is studied first due to the psycho-visual experience on this content. Then the method for objective saliency map computation with a specific contribution based on geometrical saliency is proposed. Fusion of spatial, temporal and geometric cues in an objective saliency map is realized by the multiplicative operator. Resulting objective saliency maps are evaluated against the subjective maps with promising results, highlighting interesting performance of proposed geometric saliency model.

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Section: Motivationsmentioning

confidence: 99%

Fusion of Multiple Visual Cues for Visual Saliency Extraction from Wearable Camera Settings with Strong Motion

Boujut

Benois-Pineau

Megret

2012

Computer Vision – ECCV 2012. Workshops and Demonstrations

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“…The background subtraction method has a wide range of applications in the static camera [14]. A novel framework to segment the motion objects by detecting contiguous outliers in the low-rank representation is proposed in [4,15]. It avoids the complicated motion computation by formulating the problem as outlier detection and makes use of the lowrank modeling to deal with complex background.…”

Section: Related Workmentioning

confidence: 99%

“…The parallax-based multiplanar constraint as the supplement of the epipolar constraint modifies the surface degradation to the line degradation. Compared to the previous method based on the "Plane + Parallax" framework [12][13][14][15], the parallax-based multiplanar constraint can segment the motion objects without a fixed reference plane. The main contributions can be summarized as follows.…”

Section: Introductionmentioning

confidence: 99%

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Motion Segmentation by New Three-View Constraint from a Moving Camera

Ren

et al. 2015

Mathematical Problems in Engineering

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We propose a new method for the motion segmentation using a moving camera. The proposed method classifies each image pixel in the image sequence as the background or the motion regions by applying a novel three-view constraint called the “parallax-based multiplanar constraint.” This new three-view constraint, being the main contribution of this paper, is derived from the relative projective structure of two points in three different views and implemented within the “Plane + Parallax” framework. The parallax-based multiplanar constraint overcomes the problem of the previous geometry constraint and does not require the reference plane to be constant across multiple views. Unlike the epipolar constraint, the parallax-based multiplanar constraint modifies the surface degradation to the line degradation to detect the motion objects followed by a moving camera in the same direction. We evaluate the proposed method with several video sequences to demonstrate the effectiveness and robustness of the parallax-based multiplanar constraint.

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“…Homography matrix is a global motion model which can compensate for the camera motion between consecutive video sequences. The pixel points which are consistent with homography belong to the static background [3][4][5][6][7][8]. Those inconsistent pixel points may correspond to moving objects or the parallax regions.…”

Section: Introductionmentioning

confidence: 99%

Motion object detection by three-view constraint using moving camera

Yang¹,

Gu²,

Xu³

2015

Opt Rev

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We propose a three-view constraint for the motion object detection using moving camera. The proposed method classifies feature points in the video sequence into background or motion object by applying the epipolar constraint and a novel geometric constraint called the ''three-view distance constraint''. The three-view distance constraint, being the main contribution of this paper, is derived from the relative camera poses in three different views and implemented within the detection framework. Unlike the epipolar constraint, the three-view distance constraint modifies the surface degradation to the line degradation. The three-view distance constraint is capable of detecting moving objects followed by a moving camera in the same direction. We evaluate the proposed method with several video sequences to demonstrate the effectiveness and robustness of the three-view distance constraint.

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Detection of moving foreground objects in videos with strong camera motion

Cited by 19 publications

References 23 publications

Fusion of Multiple Visual Cues for Visual Saliency Extraction from Wearable Camera Settings with Strong Motion

Fusion of Multiple Visual Cues for Visual Saliency Extraction from Wearable Camera Settings with Strong Motion

Motion Segmentation by New Three-View Constraint from a Moving Camera

Motion object detection by three-view constraint using moving camera

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