Rigid body motion from depth and optical flow
نویسندگان
چکیده
منابع مشابه
Motion and Depth from Optical Flow
Passive navigation of mobile robots is one of the challenging goals of machine vision. This note demonstrates the use of optical flow, which encodes the visual information in a sequence of time varying images [1], for the recovery of motion and the understanding of the three dimensional structure of the viewed scene. By using a modified version of an algorithm, which has recently been proposed ...
متن کاملRigid Body Segmentation and Shape Description from Dense Optical Flow under Weak Perspective Rigid Body Segmentation and Shape Description from Dense Optical Flow under Weak Perspective Summary Page
We present an algorithm for identifying and tracking independently moving rigid objects from optical ow. Some previous attempts at segmentation via optical ow have focused on nding discontinuities in the ow eld. While discontinuities do indicate a change in scene depth, they do not in general signal a boundary between two separate objects. The proposed method uses the fact that each distinct ob...
متن کاملRigid body motion from range image sequences
An algorithm is described for recovering the six degrees of freedom of motion of a vehicle from a sequence of range images of a static environment taken by a range camera rigidly attached to the vehicle. The technique utilizes a least-squares minimization of the difference between the measured rate of change of elevation at a point and the rate predicted by the so-called elevation rate constmin...
متن کاملRNG Rigid Body Motion
This note outlines how the coupling between the motion of rigid bodies immersed in a fluid and the motion of this fluid is handled in XNS. For a rigid body one has a group of nodes which define the surface of the rigid body called “reference node group” (RNG). For each RNG we save the properties of motion in arrays which in the following we will call “RNG arrays”. They contain the bottom and to...
متن کاملDepth and Flow From Motion Energy
This paper presents a model of motion perception that utilizes the output of motion-sensitive spatiotemporal filters. The power spectrum of a moving texture occupies a tilted plane in the spatiotemporal-frequency domain. The model uses 3-D (space-time) Gabor filters to sample this power spectrum. By combining the outputs of several such filters, the model estimates the velocity of the moving te...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Computer Vision, Graphics, and Image Processing
سال: 1983
ISSN: 0734-189X
DOI: 10.1016/0734-189x(83)90097-x