Simultaneous spotting of signs and fingerspellings based on hierarchical conditional random fields and boostmap embeddings
作者:
Highlights:
•
摘要
A sign language consists of two types of action; signs and fingerspellings. Signs are dynamic gestures discriminated by continuous hand motions and hand configurations, while fingerspellings are a combination of continuous hand configurations. Sign language spotting is the task of detection and recognition of signs and fingerspellings in a signed utterance. The internal structures of signs and fingerspellings differ significantly. Therefore, it is difficult to spot signs and fingerspellings simultaneously. In this paper, a novel method for spotting signs and fingerspellings is proposed. It can distinguish signs, fingerspellings and non-sign patterns, and is robust to the various sizes, scales and rotations of the signer's hand. This is achieved through a hierarchical framework consisting of three steps: (1) Candidate segments of signs and fingerspellings are discriminated using a two-layer conditional random field (CRF). (2) Hand shapes of segmented signs and fingerspellings are verified using BoostMap embeddings. (3) The motions of fingerspellings are verified in order to distinguish those which have similar hand shapes and different hand motions. Experiments demonstrate that the proposed method can spot signs and fingerspellings from utterance data at rates of 83% and 78%, respectively.
论文关键词:Sign language spotting,Fingerspelling spotting,Conditional random field
论文评审过程:Received 19 October 2009, Revised 3 March 2010, Accepted 7 March 2010, Available online 12 March 2010.
论文官网地址:https://doi.org/10.1016/j.patcog.2010.03.007