Augmentation of Perception, Movement, and Body Recognition with Tactile Sharing and Feedback and its Applications

2021 ◽  
Vol 141 (2) ◽  
pp. 80-82
Author(s):  
Yoshihiro TANAKA
Keyword(s):  
Body Recognition

Body Recognition Based on Depth Image

2014 ◽  
Vol 631-632 ◽  
pp. 414-417
Author(s):  
Jian Zhang ◽  
Wan Juan Song
Keyword(s):  
Pattern Recognition ◽  
Image Recognition ◽  
The Body ◽  
Depth Image ◽  
Body Parts ◽  
Research Status ◽  
Kinect Camera ◽  
Local Gradient ◽  
Body Recognition

The text introduces the research status of depth image in the pattern recognition and the application in the body recognition. Aiming at the problem that the image recognition shot by common camera has declined performance under the factors of illumination, posture, shielding, and the like, the body parts are distinguished and judged by taking Kinect equipment promoted by Microsoft as the platform, analyzing the features of the depth picture obtained by the Kinect camera and putting forwards to the local gradient features of comprehensive point features and the gradient features; and the elbow is taken as the example to argue simply .

scholarly journals Self-body recognition through a mirror: Easing spatial-consistency requirements for rubber hand illusion

2019 ◽  
Author(s):  
Hikaru Hasegawa ◽  
Shogo Okamoto ◽  
Ken Ito ◽  
Masayuki Hara ◽  
Noriaki Kanayama ◽  
...  
Keyword(s):  
Visual Cues ◽  
Mirror Image ◽  
Rubber Hand Illusion ◽  
Body Ownership ◽  
Rubber Hand ◽  
Subjective Evaluations ◽  
Spatial Consistency ◽  
Tactile Stimuli ◽  
Significant Difference ◽  
Body Recognition

AbstractTypical experiments to induce the rubber hand illusion (RHI) require experimental participants to gaze at a fake hand while tactile stimuli are provided to both the fake and hidden actual hands in a synchronous manner. However, under such conditions, postural and apparent disagreement between a seen fake hand and hidden actual hand prevents illusory body ownership. Provided that humans recognize mirror images as copies of the real world in spite of their spatial uncertainties or incongruence, the sensory disagreement may be accepted in RHI settings if using a mirror to show a fake hand. The present study performed two experiments to reveal how self-body recognition of a fake hand feature via mirror affects the RHI. These experiments were conducted in an RHI environment involving voluntary hand movements to investigate not only body ownership but also agency. The first experiment (Experiment 1) examined whether illusory ownership of a fake hand seen in a mirror could be induced. Then, we examined whether the RHI using a mirror image allows disagreement in orientation between the rubber and actual hands (Experiment 2). Subjective evaluations using a RHI questionnaire demonstrated that evoked embodiment of the rubber hand was stronger in the presence of a mirror than in the absence of it (Experiment 1) and that participants experienced the RHI even if the actual and rubber hands were incongruent in terms of orientation (45 °; Experiment 2). No significant difference was found in the change of perceived finger location (proprioceptive drift) between these experiments. These findings suggest that the use of a mirror masks subtle spatial incongruency or degrades the contribution of visual cues for spatial recognition and facilitates multisensory integration for bodily illusions.

Human articulated body recognition method in high-resolution monitoring images

2016 ◽  
Vol 181 ◽  
pp. 116-121 ◽  
Author(s):  
Yi Li ◽  
Xun Liu ◽  
Sanyuan Zhang ◽  
Xiuzi Ye
Keyword(s):  
High Resolution ◽  
Recognition Method ◽  
Body Recognition

A ROBUST MOVING BODY RECOGNITION METHOD

2012 ◽  
Vol 11 (02) ◽  
pp. 107-114
Author(s):  
SHOUJIA WANG ◽  
WENHUI LI ◽  
BO FU ◽  
HONGYIN NI ◽  
CONG WANG
Keyword(s):  
Computer Vision ◽  
Real Time ◽  
Connected Domain ◽  
Difference Method ◽  
Recognition Accuracy ◽  
Temporal Difference ◽  
Recognition Method ◽  
Moving Body ◽  
Robust Recognition ◽  
Body Recognition

At present, moving body recognition is one of the most active areas of research in the field of computer vision and is used widely in all kinds of videos. But the recognition accuracy of these methods has changed negatively because of the complexity of the background. In this paper, we put forward a robust recognition method. First, we obtain the moving body by tripling the temporal difference method. And then we eliminate noise from these images by mathematical morphology. Finally, we use three-scanning notation method to mark and connect the connected domain. This new method is more accurate and requires less computation in real-time experiments. The experiment result also proves its robustness.

scholarly journals A modified mark test for own-body recognition in pig-tailed macaques (Macaca nemestrina)

2010 ◽  
Vol 13 (4) ◽  
pp. 631-639 ◽  
Author(s):  
Sara Macellini ◽  
Pier Francesco Ferrari ◽  
Luca Bonini ◽  
Leonardo Fogassi ◽  
Annika Paukner
Keyword(s):  
Macaca Nemestrina ◽  
Mark Test ◽  
Body Recognition
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