A Simple and Efficient Key Frame Recognition Algorithm for Sign Language Video

2021 ◽  
pp. 3-10
Author(s):  
Zhaosong Zhu ◽  
ShengWei Zhang ◽  
YunLei Zhou
Keyword(s):  
Sign Language ◽  
Recognition Algorithm ◽  
Key Frame

Research on Continuous Sign Language Sentence Recognition Algorithm Based on Weighted Key-Frame

2018 ◽  
Vol 22 (4) ◽  
pp. 483-490
Author(s):  
Xin-Xin Xu ◽  
Yuan-Yuan Huang ◽  
Zuo-Jin Hu ◽  
◽  
Keyword(s):  
Sign Language ◽  
Adaptive Algorithm ◽  
Control Device ◽  
Recognition Algorithm ◽  
Basic Unit ◽  
Language Recognition ◽  
Sign Language Recognition ◽  
Key Frame ◽  
Sentence Recognition ◽  
Key Frames

At present, most of the dynamic sign language recognition is only for sign language words, the continuous sign language sentence recognition research and the corresponding results are less, because the segmentation of such sentence is very difficult. In this paper, a sign language sentence recognition algorithm is proposed based on weighted key-frames. Key-frames can be regarded as the basic unit of sign word, therefore, according to key frames we can get related vocabularies, and thus we can further organize these vocabularies into meaningful sentences. Such work can avoid the hard point of dividing sign language sentence directly. With the help of Kinect, i.e. motion-control device, a kind of self-adaptive algorithm of key-frame extraction based on the trajectory of sign language is brought out in the paper. After that, the key-frame is given weight according to its semantic contribution. Finally, the recognition algorithm is designed based on these weighted key-frames and thus get the continuous sign language sentence. Experiments show that the algorithm designed in this paper can realize real-time recognition of continuous sign language sentences.

scholarly journals Hand Motion-Recognition in an Intelligent Communication Module

2019 ◽  
Vol 8 (10) ◽  
pp. 151-157
Keyword(s):  
Sign Language ◽  
Research Work ◽  
Recognition Algorithm ◽  
Speech Communication ◽  
Normal Person ◽  
Hand Motion ◽  
Normal People ◽  
Static Gesture Recognition ◽  
Communication Module ◽  
Intelligent Communication

our country India consists of very high population. Almost 9 millions of population in this world can be counted as a deaf or dumb people or both. We all know that the most valuable gift from the god given to human is the capability to watch, hear, spoke & to give response as per the situation arises. We all know communication is one of the most important medium through which one may carve up his/her feelings or express the information to others. The key points in communication are ability of listening and speak the word but so many from us are unlucky because they are not gifted by this ability from the god these are deaf & dumb and people. Now a days so many researches are going on to solve difficulties of these people of our society because they had to face very hard to communicate with normal person. It is too hard for mute(deaf & dumb) people to transmit their information to the normal people. As all normal people are not fully trained to understand different sign lingo, the communication between these two types of people becomes too complex. At the time emergency or other days whenever a mute (Deaf & Dumb) people are travelling passing a message (data) becomes too hard. Due to this disability one that has hearing and speaking disability doesn’t want to stand and face the race with normal person. Since the communication for the mute people is image (Visibility), not acoustic (Audio). For these mute people Hand motion plays a very part for communication. The data transmission between mute-deaf & normal people is always a very challenging job. Deaf people make use of sign language or gestures to make understand what he/she trying to say but it is impossible to understand by hearing people. The admittance to various communication based technologies plays an essential role for these (mute) handicapped peoples. Developing a small and compressed gadget for these mute people is a difficult task. Deaf-Dumb people find a difficulty in communicating with normal people and hence they always stay apart in their societies. Basically deaf-dumb ones uses various sign language for communication, & they always face lots of difficulty while communicating with normal people because they all not able to understand sign language every time. Hence there is always a hurdle in communication between these two type of peoples. There are so many researches has done in regulate to search a simple and easy way for mute people to communicate with the normal people and articulate themselves to the rest of the real world. So many improvements have been done in sign language but all are based on American gesture (sign) Language. Our research work is purely designed to provide an aid to this deaf-mute by developing and designing a smart communication module which will help to renovate sign language to text & speech communication with other and to help them lead a life in a much better way. Our paper represents a static gesture recognition algorithm that will be designed and implemented will be used in the smart communication system to bridge the communication gap between deaf & dumb and normal people. If the algorithm is implemented completely it can be can be also used to capture and analyze emotions of the people in area where high security is desired.

A novel key-frame selection-based sign language recognition framework for the video data

2020 ◽  
Vol 68 (3) ◽  
pp. 156-169
Author(s):  
Fakhar Ullah Mangla ◽  
Aysha Bashir ◽  
Ikram Lali ◽  
Ahmad Chan Bukhari ◽  
Basit Shahzad
Keyword(s):  
Sign Language ◽  
Video Data ◽  
Language Recognition ◽  
Sign Language Recognition ◽  
Frame Selection ◽  
Key Frame ◽  
Key Frame Selection

Key Frame Extraction Algorithm of Sign Language Based on Compressed Sensing and SURF Features

2018 ◽  
Vol 55 (5) ◽  
pp. 051013
Author(s):  
王民 Wang Min ◽  
李泽洋 Li Zeyang ◽  
王纯 Wang Chun ◽  
石新源 Shi Xinyuan
Keyword(s):  
Compressed Sensing ◽  
Sign Language ◽  
Key Frame Extraction ◽  
Key Frame ◽  
Extraction Algorithm ◽  
Surf Features
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