Secondly, the backbone skeleton points of the first stage are connected according to the shortest distance of each skeleton point to the root node. Firstly, the skeleton points are extracted from the point cloud of bean plant by employing a hierarchical clustering algorithm. In this paper, we take the common grain crop legume plants in China as the research object, study the rapid three-dimensional digital reconstruction of the bean plants based on the depth images collected by the RGB-D depth camera for accurate phenotype identification. Using computer vision and image technology to digitally reconstruct plants is an important means for plant phenotyping. Results shows that the algorithm and functions of the prototype system were greatly recognized by the users with high accuracy, reasonable responding speed for real time usage.
It also verifies the accuracy of the action evaluation algorithm through comparative experiments with relevant work in recent years. This work verifies the usability and real-time performance of the algorithm and the system through a series of user experiments.
SONGHAI CHAOS CONTROL ANDROID
The work has implemented a prototype system on an Android phone. The algorithm can detect whether the user's fitness actions are standard in real time and give corresponding responses through voice. Based on the background above, this work designs a fitness action evaluation algorithm based on angle thresholds in 3D scenes which relies on cell phone monocular camera and 3D human key point detection technology. Low cost, multi-scenario virtual fitness monitoring on mobile terminal thus it made possible. With gradual maturing of human pose estimation technique, identification of human face and movements of limbs can be realized through easily accessible cell phone camera with high accuracy and speed. As a result, they fail to satisfy common needs for virtual fitness due to high cost, complexity of installation and limited application scenario.
SONGHAI CHAOS CONTROL PROFESSIONAL
Existing fitness monitoring equipment usually relies on professional hardware such as big screens, stereo camera and other sensors. However, due to the lack of action guidance and correction by professional fitness coaches, autonomous fitness usually cannot guarantee the fitness effect and is easy to cause sports injuries, so real-time monitoring of fitness actions is required.
With the increasing richness of online fitness resources, autonomous fitness has become a new sporting trend.
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