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

Abstract

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.

Motion Detection in Satellite Video

“…However, the adoption of this method require us to solve the PRC geometric model. In the literature [10], a three-view geometry was adopted to restrict and block the pseudo motions. But a continuous tracking for the corresponding points in multiple frames is needed.…”

“…Then the new compensated frame is generated, and so as to complete the global motion compensation. Two Adjacent subimages 10,1 B overlaid display after the motion compensation is shown in Figure 7, which also include the parameter-optimized high-accuracy Good Features matching point set.…”

Mono-vision based moving object detection in complex traffic scenes

“…In this area, existing approaches can be mainly structured into three main categories: Motion clustering methods [3], [4], foreground and background segmentation [5], [6] and geometric constraints based detection [7], [8], [9], [10]. Each category meets different requirements for specific applications.…”

“…On the other hand, the authors in [9] proposed an algebraic three-view geometric constraint: The structure consistency constraint that encapsulates the plane+parallax information. In [10], the authors improved this approach by replacing the epipole with a reliable tracked feature point set as reference for projective depth calculation. This modification avoids noisy information introduced by epipole estimation.…”