Moving Object Segmentation Using Optical Flow and Depth Information
نویسندگان
چکیده
This paper discusses the detection of moving objects (being a crucial part of driver assistance systems) using monocular or stereoscopic computer vision. In both cases, object detection is based on motion analysis of individually tracked image points (optical flow), providing a motion metric which corresponds to the likelihood that the tracked point is moving. Based on this metric, points are segmented into objects by employing a globally optimal graph-cut algorithm. Both approaches are comparatively evaluated using real-world vehicle image sequences.
منابع مشابه
Motion Segmentation based on On-line Non-parametric Learning using RGB-D Data
Motion segmentation is a fundamental technology in many robotic applications, such as mapping and navigation in dynamic environments. In this study, we propose a novel motion segmentation approach based on on-line non-parametric learning using RGB-D data. The proposed approach requires no prior information, such as hand-labelled initial segmentation. Foreground cues are derived from dense optic...
متن کاملMoving Objects Segmentation Using Optical Flow Estimation
In this paper, we present a new method for the segmentation of moving objects. We use one of the most powerful variational method for computing the optical flow and we exploit this information in the segmentation. This segmentation lies on well-known techniques of active contours. Since we can distinguish moving objects from static elements of a scene by analyzing norm of the optical flow vecto...
متن کاملGeneric Motion based Object Segmentation for Assisted Navigation
We propose a robust approach to annotating independently moving objects captured by head mounted stereo cameras that are worn by an ambulatory (and visually impaired) user. Initially, sparse optical flow is extracted from a single image stream, in tandem with dense depth maps. Then, using the assumption that apparent movement generated by camera egomotion is dominant, flow corresponding to inde...
متن کاملOptimize Parameters Prune LabelsOptimize Configuration Motion Edges Color Depth
This paper presents an approach to multi-object image segmentation based on object motion using Markov Random Fields. To support the information gained from motion and to achieve robustness, several additional visual cues extracted from the image data are integrated. Depth information gained from stereo disparity is included to maintain segmentation in case an segmented object stops moving. Mot...
متن کاملDetection and Segmentation of Independently Moving Objects from Dense Scene Flow
We present an approach for identifying and segmenting independently moving objects from dense scene flow information, using a moving stereo camera system. The detection and segmentation is challenging due to camera movement and non-rigid object motion. The disparity, change in disparity, and the optical flow are estimated in the image domain and the three-dimensional motion is inferred from the...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2009