Object recognition through pose and shape estimation
It provides a comparative analysis for researchers in computer vision, but it is incremental as it reviews existing methods without introducing new techniques.
This paper reviews existing state-of-the-art methods for object pose estimation, comparing their accuracy, complexity, and performance in the context of gesture and movement recognition.
Computer vision helps machines or computer to see like humans. Computer Takes information from the images and then understands of useful information from images. Gesture recognition and movement recognition are the current area of research in computer vision. For both gesture and movement recognition finding pose of an object is of great importance. The purpose of this paper is to review many state of art which is already available for finding the pose of object based on shape, based on appearance, based on feature and comparison for its accuracy, complexity and performance