First, we compare MavicPro with Phantom4. What smart features have been added to MavicPro: 1. Self-timer gestures; 2. Object recognition; 3. Parallel follow-up in visual follow-up, focus follow, and auto surround; 4. Accurate landing.
Behind every function here is to try to solve the core and the most difficult problem in the field of computer vision and robotics, and it is also the deepest hidden secret in Dajiang.
Gesture selfie
Many small drones today claim to be self-portrait drones, but in fact they all belong to the follow-up. By tracking people or faces, Dajiang achieved Phantom4 in March of this year. Today, it includes the normalized HoverCamera, etc. Drones have also achieved this function. And MavicPro is actually realizing the self-timer out of the remote control, that is, by gestures to capture.
When you come to the screen, MavicPro will identify the moving person by yourself, and you can wave it to let it follow you. If you just make a selfie during the tracking process, it will help you capture it. In this way, you can completely put the remote control in the bag during the photo taking process. And even if the tracking is lost, you can walk back to the screen without the help of the remote controller and let the aircraft continue to follow. It is worth mentioning that when GPS assistance is turned on, the aircraft will integrate GPS information to correct it.
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For the general gesture recognition system, the overall step is roughly divided into three steps, namely positioning, modeling and identification of the hand. There are two main methods of hand modeling, 2D and 3D. The main thing is to see what kind of camera is used. After modeling, it is finally recognized, such as whether your hand is open or fist. It is reported that there are different methods from the 3D hand model to gesture recognition. Some of them use the 3D hand model to identify directly, some of them convert the 3D model into 2D images, and then use deep learning to classify and recognize on this basis. At present, in the indoor environment, because of the short distance, gesture recognition is not difficult. For example, Microsoft's Kinect is well applied in video games. However, in the outdoor scene, using the camera to identify gestures on the drone at a distance, DJI should be the first attempt.
MavicPro does not use a 3D camera, but uses a 2D main camera for recognition, which is much more difficult than using a 3D camera. First of all, the aircraft needs to accurately identify and locate people in the picture without depth information. Second, it needs to complete a series of hand positioning, modeling and action recognition.
MavicPro allegedly uses deep learning, and deep learning has high requirements for computing devices. General researchers need GPUs such as NVIDIA TitanX to achieve this. The old TitanX processing performance is about 6T Flops (calculated floating point per second), and DJI is using Lianxin LC1860, the official given the total processing power at 8GFlops, a difference of about 700 times, in such a low processing platform Deep learning is faced with breakthroughs in neural network design, training techniques, streamlining and compression of models, and optimization of underlying implementation.
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