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The histogram of oriented gradients (HOG) is a feature descriptor used in computer vision and image processing for the purpose of object detection.The technique counts occurrences of gradient orientation in localized portions of an image.
The Viola–Jones object detection framework is a machine learning object detection framework proposed in 2001 by Paul Viola and Michael Jones. [1] [2] It was motivated primarily by the problem of face detection, although it can be adapted to the detection of other object classes. In short, it consists of a sequence of classifiers.
Objects detected with OpenCV's Deep Neural Network module (dnn) by using a YOLOv3 model trained on COCO dataset capable to detect objects of 80 common classes. Object detection is a computer technology related to computer vision and image processing that deals with detecting instances of semantic objects of a certain class (such as humans, buildings, or cars) in digital images and videos. [1]
Also, if the object is rotated by θ and this transformation is denoted by T θ, then T θ [R(ɸ)] = Rot{R[(ɸ-θ)mod2π],θ} i.e., all the indices are incremented by – θ modulo 2π, the appropriate vectors r are found, and then they are rotated by θ. Another property which will be useful in describing the composition of generalized Hough ...
The position of these rectangles is defined relative to a detection window that acts like a bounding box to the target object (the face in this case). In the detection phase of the Viola–Jones object detection framework , a window of the target size is moved over the input image, and for each subsection of the image the Haar-like feature is ...
The Hough transform (/ h ʌ f /) is a feature extraction technique used in image analysis, computer vision, pattern recognition, and digital image processing. [1] [2] The purpose of the technique is to find imperfect instances of objects within a certain class of shapes by a voting procedure.
All detection techniques are based on modelling the background of the image, i.e. set the background and detect which changes occur. Defining the background can be very difficult when it contains shapes, shadows, and moving objects. In defining the background, it is assumed that the stationary objects could vary in color and intensity over time.
Object recognition – technology in the field of computer vision for finding and identifying objects in an image or video sequence. Humans recognize a multitude of objects in images with little effort, despite the fact that the image of the objects may vary somewhat in different view points, in many different sizes and scales or even when they are translated or rotated.