.png){kind=icon}
返回
3D face and motion estimation from sparse points using adaptive bracketed minimization
.png){kind=icon}
PRE
AI
DOI：10.1007/s11042-011-0925-8.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
This paper presents a novel method for estimating camera motion and reconstructing human face from a video sequence. The coarse-to-fine method is applied via combining the concepts of Powell's minimization with gradient descent. Sparse points defining the human face in every frame are tracked using the active appearance model. The case of occluded points, even for self-occlusion, does not pose a problem in the proposed method. Robustness in the presence of noise and 3D accuracy using this method is also demonstrated. Examples of face reconstruction using other methods including trifocal tensor, Powell's minimization, and gradient descent are also compared to the proposed method. Experiments on both synthetic and real faces are presented and analyzed. Also, different camera movement paths are illustrated. All real-world experiments used an off-the-shelf digital camera carried by a human walking without using any dolly to demonstrate the robustness and practicality of the proposed method.
Keyword:
Camera pose
Gradient descent
Model reconstruction
Powell's multidimensional minimization
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
3
论文数:
2.0W
被引数:
3.2W
机构
引用论文
Comments on "Will greenhouse gas-induced warming over the next 50 years lead to higher frequency and greater intensity of hurricanes?"对“未来50年温室气体引起的变暖是否会导致飓风频率更高且强度更大？”的评论.png)
Tellus A
Tellus AIF0
PREAI
分享收藏分享收藏
查看更多内容