By Saad Ali, Mubarak Shah (auth.), David Forsyth, Philip Torr, Andrew Zisserman (eds.)
The four-volume set comprising LNCS volumes 5302/5303/5304/5305 constitutes the refereed lawsuits of the tenth eu convention on laptop imaginative and prescient, ECCV 2008, held in Marseille, France, in October 2008.
The 243 revised papers provided have been conscientiously reviewed and chosen from a complete of 871 papers submitted. The 4 books hide the complete diversity of present concerns in laptop imaginative and prescient. The papers are geared up in topical sections on reputation, stereo, humans and face reputation, item monitoring, matching, studying and lines, MRFs, segmentation, computational images and lively reconstruction.
Read Online or Download Computer Vision – ECCV 2008: 10th European Conference on Computer Vision, Marseille, France, October 12-18, 2008, Proceedings, Part II PDF
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Extra resources for Computer Vision – ECCV 2008: 10th European Conference on Computer Vision, Marseille, France, October 12-18, 2008, Proceedings, Part II
References 1. : SCAPE: Shape completion and animation of people. SIGGRAPH 24, 408–416 (2005) 2. : Detailed human shape and pose from images. In: CVPR (2007) 3. : Shining a light on human pose: On shadows, shading and the estimation of pose and shape. In: ICCV (2007) 4. : Accurately measuring human movement using articulated ICP with soft-joint constraints and a repository of articulated models. In: CVPR (2007) 5. : Visual hull alignment and reﬁnement across time: A 3D reconstruction algorithm combining shape-from-silhouette with stereo.
13] combine information over time by performing rigid alignment of visual hulls at diﬀerent time instants. Knowing a rigid alignment over time eﬀectively provides additional views. They also extend this idea to articulated body parts but focus only on recovering the bounding volume. Grauman et al. [14,15] estimate a 3D shape consistent with a temporal sequence of silhouettes using assumptions on the smoothness and shape transitions. They apply this method to silhouettes of humans and recover a visual hull using an example-based non-parametric model of body shapes.
5. Quantitative Evaluation. Ground truth body shapes are shown for the six subjects. For each subject the height, waist size and chest size are used for quantitative evaluation. The waist and chest are shown by red lines. Optimization Method. Unlike previous work we minimize E(β, θ) using a gradient-free direct search simplex method. For the clothing dataset, 11 canonical pose parameters θ0 were hand deﬁned and used for initialization of each pose. To help avoid local minima we alternate between optimizing pose and shape in an incremental fashion: after initializing with the predeﬁned pose and mean shape model, we begin by optimizing the global position and a few shape coeﬃcients.