Multi-sensory loss impairment (deafblindness) and Musculoskeletal disorder is increasing in humans due to genetic conditions and aging which is a great concern for future world. Patients suffering from these conditions, try to put over their message with hand gestures and poses. Many of these
PosGestix Recognizer
Multi-sensory loss impairment (deafblindness) and Musculoskeletal disorder is increasing in humans due to genetic conditions and aging which is a great concern for future world. Patients suffering from these conditions, try to put over their message with hand gestures and poses. Many of these deficiencies may be overcome by introducing a more natural human computer interaction, especially speech and gesture. In order to help these patients, so that they can live a better life, we have proposed a system which can monitor human gestures and poses, which helps these patients so that they can communicate in an effective way. We have used depth camera to detect different joint points of human body in real time and those joint points will be matched with gestures stored in database to find that what actually he or she is trying to say. Our proposed system can successfully recognize different gestures and poses in real time.
To develop a multimodal interface to manipulate the low- and high level aspects of 3D hierarchical digital models so that the hands and the face of possibly separate performers will be tracked, their gestures and facial expressions will be recognized and estimated features will be mapped to digital puppets in real-time.
The project involves tracking of hands, background segmentation, skin color filtering, particle filtering, hand pose estimation, gesture and expression and keyframe classification,
Gestures and poses are an important means of communicating in our day-to-day life. Often we communicate by the movement of body parts like hands and head rather than speaking. So for a successful machine-human interaction consideration of these gestures is inevitable. The proposed method can recognize human gestures using a depth camera. The user just need to connect camera with laptop and open the human pose and gesture recognition application and press the start button. The camera views the subject in the front plane and generates a depth image of the subject in the plane towards the camera. This depth image is then used for background removal, followed by generation of the depth profile of the subject. In addition to this, the difference between subsequent frames gives the motion profile of the subject and is used for recognition of gestures. These allow the efficient use of depth camera to successfully recognize multiple human gestures.
| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| Logitech Desktop Web Camera | Equipment | 1 | 50534 | 50534 |
| Raspberry Pi 4 | Equipment | 1 | 19200 | 19200 |
| Internet | Miscellaneous | 1 | 4000 | 4000 |
| Printing | Miscellaneous | 5 | 1000 | 5000 |
| Stationary | Miscellaneous | 8 | 100 | 800 |
| Total in (Rs) | 79534 |
Water is the very basic need of every living thing in this universe, without water we can?...
The aim of this project is to scan through the wall for any intrusion using Wi-Fi transmit...
To develop a method for contact less processing of small delicate objects in industry.&nbs...
Social media is an internet-based form of communication. Social media platforms allow user...
Increasing global population entails increasing food production. While improving productiv...