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13 Mar 2018: 10] quantize translations and rotations in twoseparate 3D arrays; peak entries in both arrays indicate thepose of the object, but multiple objects create ambiguities.Knopp et al. ... This is not practical using Hough-based approaches,due to their

13 Mar 2018: 3Note that the main requirement is that the classes are ordered so asto correctly reflect the underlying attribute-specific themes and the learntmodel maximally separates the classes while conforming to the ... all training images forattribute am, and

13 Mar 2018: Parts around the vanishing point and entry points of moving objects into the scene, suchas cross roads. ... Computational requirements The E-step in algorithm2 was implemented in C# with a 8core processor at a cost of 90s/frame.

13 Mar 2018: training data requirements, promising resultsare reported by the more recent, generalized photometric stereomethods [13,14,16] which in addition exploit class-specific con-straints of face shape and albedo. ... Fig. 6. Our offline algorithm implicitly

13 Mar 2018: 3Note that the main requirement is that the classes are ordered so asto correctly reflect the underlying attribute-specific themes and the learntmodel maximally separates the classes while conforming to the ... all training images forattribute am, and

20 Feb 2018: the dialogue and the attribute values (often called slots) thatdetermine the user’s requirements. ... eachdiscrete codebook entry b̂i.

13 Mar 2018: Divergences, also sometimes referred to as qua-sisemimetrics, form a further superset of metrics whichalso drop the requirement of sub-additivity, requiringonly conditions 1 and 2.

13 Mar 2018: training data requirements, promising resultsare reported by the more recent, generalized photometric stereomethods [13,14,16] which in addition exploit class-specific con-straints of face shape and albedo. ... Fig. 6. Our offline algorithm implicitly

13 Mar 2018: The proposed combinedscore is computed based on repeatability ratio with respectto varying accuracy requirements. ... For each detector, the detected. Table 3 For each entry, top to bottom: The average number of interestpoints detected, the average

20 Feb 2018: Foundations and Trends R inSignal ProcessingVol. 1, No. 3 (2007) 195–304c 2008 M. Gales and S. YoungDOI: 10.1561/2000000004. The Application of Hidden Markov Modelsin Speech Recognition. Mark Gales1 and Steve Young2. 1 Cambridge University

13 Mar 2018: Divergences, also sometimes referred to as qua-sisemimetrics, form a further superset of metrics whichalso drop the requirement of sub-additivity, requiringonly conditions 1 and 2.

13 Mar 2018: The proposed combinedscore is computed based on repeatability ratio with respectto varying accuracy requirements. ... For each detector, the detected. Table 3 For each entry, top to bottom: The average number of interestpoints detected, the average