The complex human activities, to the dance teaching, it has not been constrained, it is a difficult task for computer vision. Field-programmable gate array (FPGA) a classification of the movement of the Indian classical dance by using the powerful features of the built-in system tools. Human behavior recognition for this work, classical dance education in India from offline and live performance to the online control of material in the carried out of the guidance record of audio and dance, in. Another theme and 10 familiar dance of 200 m / bills have created, is the offline data of guidance form of a variety of classical dance in various postures. The data collection of a variety of topics. Or education attitude accounted for 60, Dance education in both cases. FPGA training and eight different sample size, will be performed by each of the multi-group object. The remaining two samples are tested, it has been trained on the FPGA. Different FPGA architecture design, and excellent recognition accuracy, because to get our test data. Compared to the same data set and of other classification model report, the recognition rate.

复杂的人类活动，到舞蹈教学，还没有受到限制，这对于计算机视觉来说是一项艰巨的任务。现场可编程门阵列（FPGA）通过使用内置系统工具的强大功能，对印度古典舞的动作进行了分类。对于这项工作的人类行为识别，印度的古典舞蹈教育从离线和现场表演到在线控制素材在进行音频和舞蹈的指导记录中均得到体现。另外还有主题和10种常见的200 m / bills舞蹈创建的是各种姿势的各种古典舞的指导形式的离线数据。各种主题的数据收集。或教育态度占60，两种情况下的舞蹈教育。FPGA训练和八个不同的样本量，将由每个多组对象执行。其余两个样本均经过测试，已经在FPGA上进行了培训。不同的FPGA体系结构设计，以及出色的识别精度，因为能够获得我们的测试数据。与相同数据集和其他分类模型报告相比，识别率高。