Qualitative estimation of camera motion parameters from the linear composition of optical flow

We propose a method for extracting human limb regions by the combination of optical flow-based motion segmentation and nonlinear optimization-based image registration. First, rotating limb regions with rough boundaries are extracted and motion parameters are estimated for an approximated model. Then the extracted region and estimated parameters are used as initial values for nonlinear optimization that minimizes residuals of two successive frames and estimates motion parameters. Combining the two steps reduces computational cost and avoids the initial state problem of optimization. According to estimated parameters, the limb region is extracted by a Bayesian classifier to obtain accurate region boundaries. Experimental results on real images are shown.

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Robust Software for Computing Camera Motion Parameters

Journal of Mathematical Imaging and Vision ◽

10.1007/s10851-008-0106-1 ◽

2008 ◽

Vol 33 (1) ◽

pp. 1-9 ◽

Cited By ~ 1

Author(s):

Robert Schreiber ◽

Zeyu Li ◽

Harlyn Baker

Keyword(s):

Camera Motion ◽

Motion Parameters

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Gamma Camera Motion Parameters Estimation Using Binocular Camera for Accurate Radioactive Source Image Reconstruction

2020 IEEE International Instrumentation and Measurement Technology Conference (I2MTC) ◽

10.1109/i2mtc43012.2020.9128568 ◽

2020 ◽

Author(s):

Yueer Li ◽

Zhibiao Cheng ◽

Chen Yang ◽

Mengfu Wei ◽

Junhai Wen

Keyword(s):

Image Reconstruction ◽

Gamma Camera ◽

Radioactive Source ◽

Parameters Estimation ◽

Source Image ◽

Camera Motion ◽

Motion Parameters

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Synthetic Video Generation for Evaluation of Sprite Generation

Methods and Innovations for Multimedia Database Content Management ◽

10.4018/978-1-4666-1791-9.ch010 ◽

2012 ◽

pp. 160-187

Author(s):

Yi Chen ◽

Ramazan S. Aygün

Keyword(s):

Ground Truth ◽

Objective Evaluation ◽

Camera Motion ◽

Generation Algorithm ◽

Motion Patterns ◽

Subjective Evaluations ◽

Sprite Generation ◽

Ground Truth Image ◽

Motion Parameters ◽

Synthetic Video

Sprite generation is the process of aligning, warping, and blending of pixels that belong to an object in a video. The evaluation of the correctness of a sprite is usually accomplished by a combination of objective and subjective evaluations. Availability of ground-truth image would help mere objective evaluation. In this paper, the authors present video generation from an image based on various camera motion parameters to be used as ground-truth for the sprite evaluation. This paper introduces a framework for evaluation of sprite generation algorithms. Experiments under the proposed framework were performed on the synthetic videos of different camera motion patterns to reveal the components of the sprite generation algorithm to be improved.

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