Deep Sign: Enabling Robust Statistical Continuous Sign Language Recognition via Hybrid CNN-HMMs
نویسندگان
چکیده
منابع مشابه
Deep Sign: Hybrid CNN-HMM for Continuous Sign Language Recognition
This paper introduces the end-to-end embedding of a CNN into a HMM, while interpreting the outputs of the CNN in a Bayesian fashion. The hybrid CNN-HMM combines strong discriminative abilities of CNNs with sequence modeling capabilities of HMMs. Most current approaches in the field of gesture and sign language recognition disregard the necessity of dealing with sequence data both for training a...
متن کاملTowards Continuous Sign Language Recognition with Deep Learning
Humans communicate with each other using abstract signs and symbols. While the cooperation between humans and machines can be a powerful tool for solving complex or difficult tasks, the communication must be at the abstract enough level that is both natural to the humans and understandable to the machines. Our paper focuses on natural language and in particular on sign language recognition. The...
متن کاملVideo Analysis for Continuous Sign Language Recognition
The recognition of continuous, natural signing is very challenging due to the multimodal nature of the visual cues (fingers, lips, facial expressions, body pose, etc.), as well as technical limitations such as spatial and temporal resolution and unreliable depth cues. On the other hand, signing gestures are designed to be robustly discernible. We therefore argue in favor of an integrative appro...
متن کاملRobust Person-Independent Visual Sign Language Recognition
Sign language recognition constitutes a challenging field of research in computer vision. Common problems like overlap, ambiguities, and minimal pairs occur frequently and require robust algorithms for feature extraction and processing. We present a system that performs person-dependent recognition of 232 isolated signs with an accuracy of 99.3% in a controlled environment. Person-independent r...
متن کاملRobust appearance based sign language recognition
In this work, we introduce a robust appearance-based sign language recognition system which is derived from a large vocabulary speech recognition system. The system employs a large variety of methods known from automatic speech recognition research for the modeling of temporal and language specific issues. The feature extraction part of the system is based on recent developments in image proces...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: International Journal of Computer Vision
سال: 2018
ISSN: 0920-5691,1573-1405
DOI: 10.1007/s11263-018-1121-3