Camera calibration from human motion

نویسندگان

  • Philip A. Tresadern
  • Ian D. Reid
چکیده

This paper presents a method for the self-calibration of non-rigid affine structure to a Euclidean co-ordinate frame from only two views by enforcing constraints derived from the known structure of the human body, such as piecewise rigidity and approximate symmetry. We show that the proposed algorithm is considerably more efficient yet equally accurate when compared to previous methods. The resulting structure and motion is then refined further using a full bundle adjustment to give maximum likelihood values for body segment lengths and joint angles. A quantitative analysis is presented using synthetic data whilst qualitative results are demonstrated for real examples of human motion. 2007 Elsevier B.V. All rights reserved.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Badly Calibrated Camera in Ego-motion Estimation, Propagation of Uncertainty Badly Calibrated Camera in Ego-motion Estimation { Propagation of Uncertainty ?

Reference Tomm a s Svoboda and Peter Sturm. A badly calibrated camera in ego-motion estimation, propagation of uncertainty. Abstract. This paper deals with the ego-motion estimation (motion of the camera) from two views. To estimate an ego-motion we have to nd correspondences and we need a calibrated camera. In this paper we solve the problem how to propagate known camera calibration errors int...

متن کامل

Comparison of Self-Calibration Algorithms for Moving Cameras

English It is an important requirement for many computer vision applications that the imaging parameters of a camera used for image acquisition are known. The intrinsic and extrinsic parameters of the camera models the mapping between the scene and the images. If the values of these parameters are available, the camera is calibrated. Traditional methods for camera calibration use special patter...

متن کامل

Self-Calibration of a Camera from Video of a Walking Human

Analysis of human activity from a video camera is simplified by the knowledge of the camera’s intrinsic and extrinsic parameters. We describe a technique to estimate such parameters from image observations without requiring measurements of scene objects. We first develop a general technique for calibration using vanishing points and vanishing line. We then describe a method for estimating the n...

متن کامل

What Precision with a Badly CalibratedCamera in

This paper deals with the ego-motion estimation (motion of the camera) from two views. When we want to estimate the ego-motion we have to nd correspondences and we need a calibrated camera. In this paper we solve the problem how to propagate known camera calibration errors into the uncertainty of the motion parameters. We present a linear estimate of the uncertainty of the motion parameters bas...

متن کامل

Ambiguities in Camera Self-Calibration

Structure from motion (SfM) is the problem of computing the 3D scene and camera parameters from a video or collection of images. SfM can be further classified as calibrated and un-calibrated. In calibrated SfM, the internal camera parameters are known. This is a much easier problem than the un-calibrated case, where these parameters are unknown. Solving for the internal camera parameters are kn...

متن کامل

Underwater Vehicle Motion Parameters Estimation Simulation and Experiment Based on Monocular Vision and Low Cost Inertial Measurement Unit

In this paper, authors proposed a practical motion estimation strategy to obtain the single static object position and the vehicle’s motion parameters simultaneously by utilizing camera and IMU (Inertial Measurement Unit), and tried several classic nonlinear parameters estimation methods on this problem based on the Matlab simulation. A lot of preliminary calibration experiments have been done ...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:
  • Image Vision Comput.

دوره 26  شماره 

صفحات  -

تاریخ انتشار 2008