&lt;title&gt;Total least squares fitting spatiotemporal derivatives to smooth optical flow fields&lt;/title&gt;

Wang, Shenq; Markandey, Vishal; Reid, Anthony

doi:10.1117/12.139397

Cited by 18 publications

(7 citation statements)

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“…which is identical to the TLS form used in [8][9][10]. In turn the equivalent probability distribution for (u, v) is shown in Fig.…”

Section: Probabilistic Brightness Constraintmentioning

confidence: 91%

Revisiting the Brightness Constraint: Probabilistic Formulation and Algorithms

Govindu

2006

Computer Vision – ECCV 2006

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Abstract. In this paper we introduce a principled approach to modeling the image brightness constraint for optical flow algorithms. Using a simple noise model, we derive a probabilistic representation for optical flow. This representation subsumes existing approaches to flow modeling, provides insights into the behaviour and limitations of existing methods and leads to modified algorithms that outperform other approaches that use the brightness constraint. Based on this representation we develop algorithms for flow estimation using different smoothness assumptions, namely constant and affine flow. Experiments on standard data sets demonstrate the superiority of our approach.

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“…which is identical to the TLS form used in [8][9][10]. In turn the equivalent probability distribution for (u, v) is shown in Fig.…”

Section: Probabilistic Brightness Constraintmentioning

confidence: 91%

Revisiting the Brightness Constraint: Probabilistic Formulation and Algorithms

Govindu

2006

Computer Vision – ECCV 2006

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“…First, the vector V3 is a homogeneous representation of the total least squares solution for the optic flow [11]. Second, the ratio of the eigenvalues e2/e3 indicates how well the derivative measurements fit the optic flow defined by V3…”

Section: A Local Spatio-temporal Image Statisticsmentioning

confidence: 99%

Advances in Security Technologies: Imaging, Anomaly Detection, and Target and Biometric Recognition

O'Sullivan

Pless

2007

2007 IEEE/MTT-S International Microwave Symposium

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Security system design and analysis are constantly improving. There are advances in sensors, in system concept, and in signal and image processing that all contribute to these improvements. Several of these advances are discussed, with an emphasis on imaging sensors with a wide range of wavelengths and deployment scenarios. In order for a security system to provide timely, reliable information, the processing must be efficient and robust. Specific, yet generalizable, developments in surveillance systems and in recognition systems are detailed.

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“…3 is a homogeneous representation of the total least squares solution [11,20,21], for the optic flow. The 2-d flow vector ( f x , f y ) can be written:…”

Section: Representing the Distribution Of Derivativesmentioning

confidence: 99%

Detecting Roads in Stabilized Video with the Spatio-Temporal Structure Tensor

Pless

2006

Geoinformatica

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Video provides strong cues for automatic road extraction that are not available in static aerial images. In video from a static camera, or stabilized (or geo-referenced) aerial video data, motion patterns within a scene enable function attribution of scene regions. A Broad,^for example, may be defined as a path of consistent motionVa definition which is valid in a large and diverse set of environments. The spatiotemporal structure tensor field is an ideal representation of the image derivative distribution at each pixel because it can be updated in real time as video is acquired. An eigen-decomposition of the structure tensor encodes both the local scene motion and the variability in the motion. Additionally, the structure tensor field can be factored into motion components, allowing explicit determination of traffic patterns in intersections. Example results of a real time system are shown for an urban scene with both well-traveled and infrequently traveled roads, indicating that both can be discovered simultaneously. The method is ideal in urban traffic scenes, which are the most difficult to analyze using static imagery.

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<title>Total least squares fitting spatiotemporal derivatives to smooth optical flow fields</title>

Cited by 18 publications

References 0 publications

Revisiting the Brightness Constraint: Probabilistic Formulation and Algorithms

Revisiting the Brightness Constraint: Probabilistic Formulation and Algorithms

Advances in Security Technologies: Imaging, Anomaly Detection, and Target and Biometric Recognition

Detecting Roads in Stabilized Video with the Spatio-Temporal Structure Tensor

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