DietCam: Automatic dietary assessment with mobile camera phones

Obesity has become a severe health problem in developed countries, and a healthy food intake has been recognized as the key factor for obesity prevention. This paper presents a mobile phone based system, DietCam, to help assess food intakes with few human interventions. DietCam only requires users to take three images or a short video around the meal, then it will do the rest. The experiments of DietCam in real restaurants verify the possibility of food recognition with vision techniques.

[1]  Trevor Darrell,et al.  Unsupervised feature selection via distributed coding for multi-view object recognition , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.

[2]  Subhransu Maji,et al.  Multiple-view object recognition in band-limited distributed camera networks , 2009, 2009 Third ACM/IEEE International Conference on Distributed Smart Cameras (ICDSC).

[3]  K. Patrick,et al.  Health and the mobile phone. , 2008, American journal of preventive medicine.

[4]  Anil K. Jain,et al.  Feature extraction methods for character recognition-A survey , 1996, Pattern Recognit..

[5]  Xavier Armangué,et al.  A comparative review of camera calibrating methods with accuracy evaluation , 2002, Pattern Recognit..

[6]  Zhaolin Cheng,et al.  Determining Vision Graphs for Distributed Camera Networks Using Feature Digests , 2007, EURASIP J. Adv. Signal Process..

[7]  David S. Ebert,et al.  Automatic portion estimation and visual refinement in mobile dietary assessment , 2010, Electronic Imaging.

[8]  Richard Szeliski,et al.  A Comparison and Evaluation of Multi-View Stereo Reconstruction Algorithms , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

[9]  Richard Szeliski,et al.  A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms , 2001, International Journal of Computer Vision.

[10]  David G. Lowe,et al.  Object recognition from local scale-invariant features , 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision.

[11]  Jindong Tan,et al.  A 3D object model for wireless camera networks with network constraints , 2013 .

[12]  Ashutosh Saxena,et al.  3-D Reconstruction from Sparse Views using Monocular Vision , 2007, 2007 IEEE 11th International Conference on Computer Vision.

[13]  E. Finkelstein,et al.  National medical spending attributable to overweight and obesity: how much, and who's paying? , 2003, Health affairs.

[14]  Alex Pentland,et al.  3D structure from 2D motion , 1999, IEEE Signal Process. Mag..

[15]  Tammy Toscos,et al.  Chick clique: persuasive technology to motivate teenage girls to exercise , 2006, CHI Extended Abstracts.

[16]  William G. Griswold,et al.  Usability and Feasibility of PmEB: A Mobile Phone Application for Monitoring Real Time Caloric Balance , 2006, Mob. Networks Appl..

[17]  Tsuhan Chen,et al.  A Probabilistic Framework for Geometry Reconstruction using Prior Information , 2007, 2007 IEEE International Conference on Image Processing.

[18]  David G. Lowe,et al.  Object Class Recognition with Many Local Features , 2004, 2004 Conference on Computer Vision and Pattern Recognition Workshop.

[19]  Pradeep Buddharaju,et al.  NEAT-o-Games: blending physical activity and fun in the daily routine , 2008, CIE.

[20]  David Nistér,et al.  Scalable Recognition with a Vocabulary Tree , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

[21]  Bernt Schiele,et al.  Local features for object class recognition , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.

[22]  Cordelia Schmid,et al.  Scale & Affine Invariant Interest Point Detectors , 2004, International Journal of Computer Vision.

[23]  G. Strang Introduction to Linear Algebra , 1993 .

[24]  O. C. Zienkiewicz,et al.  The Finite Element Method for Solid and Structural Mechanics , 2013 .

[25]  Ashutosh Saxena,et al.  Make3D: Learning 3D Scene Structure from a Single Still Image , 2009, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[26]  Zhengyou Zhang,et al.  Flexible camera calibration by viewing a plane from unknown orientations , 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision.

[27]  J.O. Hill Novel engineering approaches to obesity, overweight, and energy balance: public health needs and research opportunities , 2004, The 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[28]  Rodrigo de Oliveira,et al.  TripleBeat: enhancing exercise performance with persuasion , 2008, Mobile HCI.

[29]  Deborah Estrin,et al.  Image browsing, processing, and clustering for participatory sensing: lessons from a DietSense prototype , 2007, EmNets '07.