文章基本信息

标题：Retrieval-Combination Approach to Estimate 3D Human Pose from Monocular Image
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作者：Hui Cao ; Noboru Ohnishi ; Yoshinori Takeuchi 等
期刊名称：Information and Media Technologies
电子版ISSN：1881-0896
出版年度：2007
卷号：2
期号：3
页码：723-733
DOI：10.11185/imt.2.723
出版社：Information and Media Technologies Editorial Board
摘要：A 3D human pose is estimated from a monocular image using a retrieval-combination approach that exploits the broad capability of example-based approaches and the flexibility of parts-based approaches. Instead of storing and searching for similar full-body examples, we adopt a half-body representation (i.e., either upper-body or lower-body) to reduce a large full-body database into a compact half-body database. The database can create millions of poses by valid half-body combinations. For a given query image, half-body candidates are first retrieved from the database by partial-shape matching. Valid half-body combinations of these candidates are selected based on a learned combination constraint, and then the optimal combination(s) is(are) chosen in a coarse-to-fine evaluation method. We show good experimental results for estimating poses with both synthetic and real images. Our approach has less time and space complexities than example-based approaches and ensures more realistic 3D pose estimates than those of parts-based approaches.
关键词：Human Pose Estimation;Half-body Combination;Chamfer Distance;Image Retrieval