Object Detection with Heuristic Coarse-to-Fine Search

An improved corn wet milling process is disclosed. In a process in which corn kernels are steeped in an aqueous solution and are milled to facilitate the separation of the components thereof, in which starch from the corn is separated from gluten, and in which at least one aqueous gluten-containing stream is generated, the improvement comprises membrane filtration of an aqueous gluten-containing stream, producing a gluten-enriched retentate, and removing water from the gluten-enriched retentate, thereby producing a substantially dry gluten product. This improved process provides an economical means of recovering a higher percentage of the available protein for inclusion in high value products.

[1]  Martin A. Fischler,et al.  The Representation and Matching of Pictorial Structures , 1973, IEEE Transactions on Computers.

[2]  Nils J. Nilsson,et al.  Principles of Artificial Intelligence , 1980, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[3]  Daniel P. Huttenlocher,et al.  Comparing Images Using the Hausdorff Distance , 1993, IEEE Trans. Pattern Anal. Mach. Intell..

[4]  Umesh V. Vazirani,et al.  An Introduction to Computational Learning Theory , 1994 .

[5]  Olga Veksler,et al.  Fast approximate energy minimization via graph cuts , 2001, Proceedings of the Seventh IEEE International Conference on Computer Vision.

[6]  Yali Amit,et al.  A Computational Model for Visual Selection , 1999, Neural Computation.

[7]  Daniel Snow,et al.  Efficient Deformable Template Detection and Localization without User Initialization , 2000, Comput. Vis. Image Underst..

[8]  Paul A. Viola,et al.  Rapid object detection using a boosted cascade of simple features , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[9]  Yali Amit,et al.  2D Object Detection and Recognition , 2002 .

[10]  Alan L. Yuille,et al.  Bayesian A Tree Search with Expected O(N) Node Expansions: Applications to Road Tracking , 2002, Neural Computation.

[11]  Pietro Perona,et al.  Object class recognition by unsupervised scale-invariant learning , 2003, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings..

[12]  Dan Klein,et al.  A* Parsing: Fast Exact Viterbi Parse Selection , 2003, NAACL.

[13]  Donald Geman.  Coarse-to-Fine Classification and Scene Labeling , 2003 .

[14]  Donald Geman,et al.  Coarse-to-Fine Face Detection , 2004, International Journal of Computer Vision.

[15]  Daniel P. Huttenlocher,et al.  Pictorial Structures for Object Recognition , 2004, International Journal of Computer Vision.

[16]  Yali Amit,et al.  A coarse-to-fine strategy for multiclass shape detection , 2004, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[17]  Pietro Perona,et al.  A sparse object category model for efficient learning and exhaustive recognition , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

[18]  Jonathan Brandt,et al.  Robust object detection via soft cascade , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

[19]  Bill Triggs,et al.  Histograms of oriented gradients for human detection , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

[20]  Jianguo Zhang,et al.  The PASCAL Visual Object Classes Challenge , 2006 .

[21]  David Ellis,et al.  Multilevel Coarse-to-Fine PCFG Parsing , 2006, NAACL.

[22]  Navneet Dalal,et al.  Finding People in Images and Videos , 2006 .

[23]  Cristian Sminchisescu,et al.  Training Deformable Models for Localization , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

[24]  Daniel P. Huttenlocher,et al.  Weakly Supervised Learning of Part-Based Spatial Models for Visual Object Recognition , 2006, ECCV.

[25]  Cordelia Schmid,et al.  Local Features and Kernels for Classification of Texture and Object Categories: A Comprehensive Study , 2006, 2006 Conference on Computer Vision and Pattern Recognition Workshop (CVPRW'06).

[26]  David A. McAllester,et al.  The Generalized A* Architecture , 2007, J. Artif. Intell. Res..

[27]  Paul A. Viola,et al.  Multiple-Instance Pruning For Learning Efficient Cascade Detectors , 2007, NIPS.

[28]  Ross Girshick,et al.  Discriminatively Trained Mixtures of Deformable Part Models , 2008 .

[29]  Christoph H. Lampert,et al.  Beyond sliding windows: Object localization by efficient subwindow search , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.

[30]  David A. McAllester,et al.  A discriminatively trained, multiscale, deformable part model , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.

[31]  David A. McAllester,et al.  Object Detection with Discriminatively Trained Part Based Models , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[32]  M. Zeldin.  Heuristics! , 2010 .