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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.


Papers
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Journal ArticleDOI
TL;DR: It is shown that the neural response properties at the system level should be adjusted to the changing statistics of the input so as to maximize information transmission, and that this principle accounts for several well-documented psychophysical phenomena, including the tilt aftereffect.

238 citations

Patent
12 Apr 1996
TL;DR: In this paper, an electronic still camera is provided with an electronic image sensor for generating an image signal corresponding to a still image of a subject and an orientation determination section for sensing the orientation of the camera relative to the subject.
Abstract: An electronic still camera is provided with an electronic image sensor for generating an image signal corresponding to a still image of a subject and an orientation determination section for sensing the orientation of the camera relative to the subject. The orientation determination section provides an orientation signal recognizing either the vertical or the horizontal orientation of the camera relative to the subject. An image processor is responsive to the orientation signal for processing the image signal and correcting the orientation thereof so that the still image is output from the image processor in a predetermined orientation. In this way, the electronic still camera can be positioned in a variety of orientations relative to a subject, including both clockwise and counterclockwise vertical "portrait" orientations and a horizontal "landscape" orientation, without affecting the orientation of the images output by the camera.

238 citations

Proceedings ArticleDOI
02 May 2014
TL;DR: A new compact image pyramid representation, the Riesz pyramid, that can be used for real-time phase-based motion magnification and is less overcomplete than even the smallest two orientation, octave-bandwidth complex steerable pyramid, and can be implemented using compact, efficient linear filters in the spatial domain.
Abstract: We present a new compact image pyramid representation, the Riesz pyramid, that can be used for real-time phase-based motion magnification. Our new representation is less overcomplete than even the smallest two orientation, octave-bandwidth complex steerable pyramid, and can be implemented using compact, efficient linear filters in the spatial domain. Motion-magnified videos produced with this new representation are of comparable quality to those produced with the complex steerable pyramid. When used with phase-based video magnification, the Riesz pyramid phase-shifts image features along only their dominant orientation rather than every orientation like the complex steerable pyramid.

237 citations

Journal ArticleDOI
TL;DR: A segmentation algorithm using deformable template models to segment a vehicle of interest both from the stationary complex background and other moving vehicles in an image sequence is proposed and solved by the Metropolis algorithm.
Abstract: This paper proposes a segmentation algorithm using deformable template models to segment a vehicle of interest both from the stationary complex background and other moving vehicles in an image sequence. We define a polygonal template to characterize a general model of a vehicle and derive a prior probability density function to constrain the template to be deformed within a set of allowed shapes. We propose a likelihood probability density function which combines motion information and edge directionality to ensure that the deformable template is contained within the moving areas in the image and its boundary coincides with strong edges with the same orientation in the image. The segmentation problem is reduced to a minimization problem and solved by the Metropolis algorithm. The system was successfully tested on 405 image sequences containing multiple moving vehicles on a highway.

237 citations

Proceedings ArticleDOI
04 Dec 1990
TL;DR: A two-dimensional version of the approach is developed which has the property of being able to represent multiple edges at the same location and determine the orientation of each to any desired precision, which permits junctions to be localized without rounding.
Abstract: The projection of depth or orientation discontinuities in a physical scene results in image intensity edges which are not ideal step edges but are more typically a combination of step, peak and roof profiles. Most edge detection schemes ignore the composite nature of these edges, resulting in systematic errors in detection and localization. The problem of detecting and localizing these edges is addressed, along with the problem of false responses in smoothly shaded regions with constant gradient of the image brightness. A class of nonlinear filters, known as quadratic filters, is appropriate for this task, while linear filters are not. Performance criteria are derived for characterizing the SNR, localization and multiple responses of these filters in a manner analogous to Canny's criteria for linear filters. A two-dimensional version of the approach is developed which has the property of being able to represent multiple edges at the same location and determine the orientation of each to any desired precision. This permits junctions to be localized without rounding. Experimental results are presented. >

237 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202212
2021535
2020771
2019830
2018727
2017691