Browsing by Subject "motion capture"

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Open Access
Example-based retargeting of human motion to arbitrary mesh models
(Blackwell Publishing Ltd, 2015) Celikcan, U.; Yaz I.O.; Capin, T.
We present a novel method for retargeting human motion to arbitrary 3D mesh models with as little user interaction as possible. Traditional motion-retargeting systems try to preserve the original motion, while satisfying several motion constraints. Our method uses a few pose-to-pose examples provided by the user to extract the desired semantics behind the retargeting process while not limiting the transfer to being only literal. Thus, mesh models with different structures and/or motion semantics from humanoid skeletons become possible targets. Also considering the fact that most publicly available mesh models lack additional structure (e.g. skeleton), our method dispenses with the need for such a structure by means of a built-in surface-based deformation system. As deformation for animation purposes may require non-rigid behaviour, we augment existing rigid deformation approaches to provide volume-preserving and squash-and-stretch deformations. We demonstrate our approach on well-known mesh models along with several publicly available motion-capture sequences. We present a novel method for retargeting human motion to arbitrary 3D mesh models with as little user interaction as possible. Traditional motion-retargeting systems try to preserve the original motion, while satisfying several motion constraints. Our method uses a few pose-to-pose examples provided by the user to extract the desired semantics behind the retargeting process while not limiting the transfer to being only literal. Thus, mesh models with different structures and/or motion semantics from humanoid skeletons become possible targets. © 2014 The Eurographics Association and John Wiley & Sons Ltd.
Open Access
A hybrid approach for human motion retrieval
(2015) Salor, Yağız
Retrieving similar motions from motion databases has become an essential topic of computer animation research. The use of binary geometric features and inverted indexes is one of the efficient solutions to this problem. This approach can be used with variation and inexactness algorithms for fuzzy searches. However, close similarity searches are not possible. In addition, the process is not automatic since it needs user input for selecting binary features to use. In another efficient approach, k-d tree with medium sized numerical based feature sets and shortest path search on a directed graph are used. However, it does not propose any tool for fuzzy searches. In this thesis, we propose a hybrid approach that utilizes numerical based feature sets, k-d tree based indexing structure and inverted index based motion matching technique. Our hybrid approach does not need user input, can be used in environments requiring close similarity of motions and can be used with variation and inexactness algorithms. Our results show that our hybrid approach is useful and efficient for similarity searches on motion databases.