Real time tracking of the human body

Submission history
Contents:
  1. Pfinder : real-time tracking of the human body
  2. Sony's 'Real-time tracking' is a big leap forward for autofocus
  3. A GPS for inside your body
  4. References
  5. Advanced Realtime Tracking

Pfinder : real-time tracking of the human body

We are excited to release a TensorFlow Lite sample application for human pose estimation on Android using the PoseNet model. PoseNet is a vision model that estimates the pose of a person in an image or video by detecting the positions of key body parts.

The pose estimation model does not identify who is in an image; only the positions of key body parts. Check out the source code! There are many possibilities with pose estimation. To name a few, developers can augment reality based on images of the body, animate computer graphic characters , and analyze the gait of athletes in sports. This sample application will make it easier for app developers and machine learning experts to explore the possibilities of a light-weight mobile model. In contrast with the existing Android examples that are written in Java, the PoseNet sample app was developed in Kotlin.

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Sony's 'Real-time tracking' is a big leap forward for autofocus

The goal of developing the app was to make it easy for anyone to use the PoseNet model with minimal overhead. The sample app includes a PoseNet library that abstracts away the complexities of the model. The diagram below shows the workflow between the application, PoseNet library, and TensorFlow Lite library. The Person class contains the locations of the key body parts with their associated confidence scores.

The team used a wireless technology that they've previously demonstrated to detect heart rate, breathing and movement. Interestingly, the marker inside the body does not need to transmit any wireless signal.


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It simply reflects the signal transmitted by a device outside the body, without needing a battery or any other external source of energy. A key challenge in using wireless signals in this way is the many competing reflections that bounce off a person's body. In fact, the signals that reflect off a person's skin are actually million times more powerful than the signals of the metal marker itself. To overcome this, the team designed an approach that essentially separates the interfering skin signals from the ones they're trying to measure. They did this using a small semiconductor device called a "diode" that can mix signals together so that the team can then filter out the skin-related signals.

A GPS for inside your body

When all of the signals reflect back to the system, the system only picks up the combined frequencies , thereby filtering out the original frequencies that came from the patient's skin. ReMix makes a leap in this direction by showing that the wireless component of implantable devices may no longer be the bottleneck. One potential application for ReMix is in proton therapy, a type of cancer treatment that involves bombarding tumors with beams of magnet-controlled protons.

The approach allows doctors to prescribe higher doses of radiation, but requires a very high degree of precision, which means that it's usually limited to only certain cancers. Its success hinges on something that's actually quite unreliable: a tumor staying exactly where it is during the radiation process.

To overcome this, the team designed an approach that essentially separates the interfering skin signals from the ones they're trying to measure. They did this using a small semiconductor device called a "diode" that can mix signals together so that the team can then filter out the skin-related signals.

References

When all of the signals reflect back to the system, the system only picks up the combined frequencies , thereby filtering out the original frequencies that came from the patient's skin. ReMix makes a leap in this direction by showing that the wireless component of implantable devices may no longer be the bottleneck.

One potential application for ReMix is in proton therapy, a type of cancer treatment that involves bombarding tumors with beams of magnet-controlled protons.


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  5. The approach allows doctors to prescribe higher doses of radiation, but requires a very high degree of precision, which means that it's usually limited to only certain cancers. Its success hinges on something that's actually quite unreliable: a tumor staying exactly where it is during the radiation process.

    Advanced Realtime Tracking

    If a tumor moves, then healthy areas could be exposed to the radiation. But with a small marker like ReMix's, doctors could better determine the location of a tumor in real-time, and be able to either pause the treatment or steer the beam into the right position to deal with the movement.

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    To be clear, ReMix is not yet accurate enough to be used in clinical settings -- Katabi says a margin of error closer to a couple of millimeters would be necessary for actual implementation. There are still many challenges ahead for improving ReMix. The team next hopes to combine the wireless data with medical information like MRI scans to further improve the system's accuracy.