请问这个thread 的构造方法是怎么实现的

在看realsense的官方例程代码 发现一个看不懂的thread 构造方法
有没有懂的解释一下,网上也没有找到
这个 thread ( [&] () {code}) 是什么使用方法?


std::thread processing_thread([&]() {
        while (!stopped) //While application is running
        {
            rs2::frameset data = pipe.wait_for_frames(); // Wait for next set of frames from the camera
            rs2::frame depth_frame = data.get_depth_frame(); //Take the depth frame from the frameset
            if (!depth_frame) // Should not happen but if the pipeline is configured differently
                return;       //  it might not provide depth and we don't want to crash

            rs2::frame filtered = depth_frame; // Does not copy the frame, only adds a reference

            /* Apply filters.
            The implemented flow of the filters pipeline is in the following order:
            1. apply decimation filter
            2. apply threshold filter
            3. transform the scene into disparity domain
            4. apply spatial filter
            5. apply temporal filter
            6. revert the results back (if step Disparity filter was applied
            to depth domain (each post processing block is optional and can be applied independantly).
            */
            bool revert_disparity = false;
            for (auto&& filter : filters)
            {
                if (filter.is_enabled)
                {
                    filtered = filter.filter.process(filtered);
                    if (filter.filter_name == disparity_filter_name)
                    {
                        revert_disparity = true;
                    }
                }
            }
            if (revert_disparity)
            {
                filtered = disparity_to_depth.process(filtered);
            }

            // Push filtered & original data to their respective queues
            // Note, pushing to two different queues might cause the application to display
            //  original and filtered pointclouds from different depth frames
            //  To make sure they are synchronized you need to push them together or add some
            //  synchronization mechanisms
            filtered_data.enqueue(filtered);
            original_data.enqueue(depth_frame);
        }
    });

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