METHOD AND SYSTEM FOR DETECTING CHANGE OF CONTEXT IN VIDEO STREAMS

Described is a system for detecting change of context in a video stream on an autonomous platform. The system extracts salient patches from image frames in the video stream. Each salient patch is translated to a concept vector. A recurrent neural network is enervated with the concept vector, resulting in activations of the recurrent neural network. The activations are classified, and the classified activations are mapped onto context classes. A change in context class is detected in the image frames, and the system causes the autonomous platform to perform an automatic operation to adapt to the change of context class. 描述了一种在自主平台上对视频流中的上下文变化进行检测的系统。所述系统从视频流中的图像帧提取显著块。各个显著块被转换成概念向量。利用概念向量使循环神经网络复苏，从而产生循环神经网络的激活。对激活进行分类，并且将所分类的激活映射至上下文类。在图像帧中对上下文类变化进行检测，并且所述系统使自主平台进行自动操作，以适应上下文类变化。