Face Landmark Detection is a Computer Vision task to detect and track key points on a human face. These landmarks help to localize important regions of the face, like eyes, eyebrows, nose, jaw and mouth. Know more on this thread: 🧵
These landmarks are useful in various modern day applications like:
Face Morphing
Face Animation
Since most of the applications of Face Landmark Detection find their use in mobile phone devices, requiring low processing latency and data privacy, often simple Machine Learning approaches are preferred.
In my latest video, you would get to learn one such Machine Learning technique called Local Binary Features. The main component of this technique Random Regression Forests are also discussed in the video.
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Other than topics, ROS (Robot Operating System) uses two more modes of communication between the independent nodes of the ROS Graph are Services and Actions. Let’s discuss more about them in this thread. 🧵
Services implement a synchronous Remote Procedure Call to exchange data. The server (which provides the service) specifies a callback function to deal with the service request, and advertises the service. The client (which calls the service) then accesses the service.
Service calls are well suited for procedures that are done occasionally and take a bounded amount of time to complete. For instance, in the Gazebo simulator, robot models are spawned by calling a spawn service.