Orientation (computer vision)

About: Orientation (computer vision) is a research topic. Over the lifetime, 17196 publications have been published within this topic receiving 358181 citations.

A novel method for detecting lips, eyes and faces in real time

Abstract: This paper presents a real-time face detection algorithm for locating faces in images and videos. This algorithm finds not only the face regions, but also the precise locations of the facial components such as eyes and lips. The algorithm starts from the extraction of skin pixels based upon rules derived from a simple quadratic polynomial model. Interestingly, with a minor modification, this polynomial model is also applicable to the extraction of lips. The benefits of applying these two similar polynomial models are twofold. First, much computation time are saved. Second, both extraction processes can be performed simultaneously in one scan of the image or video frame. The eye components are then extracted after the extraction of skin pixels and lips. Afterwards, the algorithm removes the falsely extracted components by verifying with rules derived from the spatial and geometrical relationships of facial components. Finally, the precise face regions are determined accordingly. According to the experimental results, the proposed algorithm exhibits satisfactory performance in terms of both accuracy and speed for detecting faces with wide variations in size, scale, orientation, color, and expressions.

System and method of improving the legibility and applicability of document pictures using form based image enhancement

Abstract: A system and method for imaging a document, and using a reference document to place pieces of the document in their correct relative position and resize such pieces in order to generate a single unified image, including the electronic capturing a document with one or multiple images using an imaging device, the performing of pre-processing of said images to optimize the results of subsequent image recognition, enhancement, and decoding, the comparing of said images against a database of reference documents to determine the most closely fitting reference document, and the applying of knowledge from said closely fitting reference document to adjust geometrically the orientation, shape, and size of said electronically captured images so that said images correspond as closely as possibly to said reference document.

An active vision system for fall detection and posture recognition in elderly healthcare

Abstract: The paper presents an active vision system for the automatic detection of falls and the recognition of several postures for elderly homecare applications. A wall-mounted Time-Of-Flight camera provides accurate measurements of the acquired scene in all illumination conditions, allowing the reliable detection of critical events. Preliminarily, an off-line calibration procedure estimates the external camera parameters automatically without landmarks, calibration patterns or user intervention. The calibration procedure searches for different planes in the scene selecting the one that accomplishes the floor plane constraints. Subsequently, the moving regions are detected in real-time by applying a Bayesian segmentation to the whole 3D points cloud. The distance of the 3D human centroid from the floor plane is evaluated by using the previously defined calibration parameters and the corresponding trend is used as feature in a thresholding-based clustering for fall detection. The fall detection shows high performances in terms of efficiency and reliability on a large real dataset in which almost one half of events are falls acquired in different conditions. The posture recognition is carried out by using both the 3D human centroid distance from the floor plane and the orientation of the body spine estimated by applying a topological approach to the range images. Experimental results on synthetic data validate the correctness of the proposed posture recognition approach.

Method for detecting rotation and magnification in images

Abstract: A method for detecting an amount of rotation or magnification in a modified image, includes the steps of: embedding a marker image having a pair of identical features separated by a distance d and oriented at an angle α in an original image to produce a marked image, the marked image having been rotated and/or magnified to produce the modified image; performing an autocorrelation on the modified image to produce a pair of autocorrelation peaks corresponding to the location of the features of the marker image in the modified image; and comparing the separation d' and orientation α' of the autocorrelation peaks with the separation d and orientation α of the features in the marker image to determine the amount of rotation and magnification in the modified image.

A Multi-Orientation Analysis Approach to Retinal Vessel Tracking

Abstract: This paper presents a method for retinal vasculature extraction based on biologically inspired multi-orientation analysis. We apply multi-orientation analysis via so-called invertible orientation scores, modeling the cortical columns in the visual system of higher mammals. This allows us to generically deal with many hitherto complex problems inherent to vessel tracking, such as crossings, bifurcations, parallel vessels, vessels of varying widths and vessels with high curvature. Our approach applies tracking in invertible orientation scores via a novel geometrical principle for curve optimization in the Euclidean motion group SE(2). The method runs fully automatically and provides a detailed model of the retinal vasculature, which is crucial as a sound basis for further quantitative analysis of the retina, especially in screening applications.