Visual Recognition and Search

EECS 6890 Topics in Information Processing (3 Credits)

Instructors: Rogerio Feris, Liangliang Cao, and Jun Wang

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Important Dates

Class Topic
Required Reading
Jan 23
CLASS 1 - Introduction [Rogerio]
SLIDES CLASS 1 [Rogerio]
Jan 30
CLASS 2 - Machine Learning Fundamentals [Jun]
This class will review basic concepts of machine learning. Check COMS 4771 Machine Learning for related topics and tutorials.
 Part I: From Low-level to Semantic Visual Representations
Feb 06
CLASS 3 - Low-level Feature Detection and Description [Liangliang]
SLIDES CLASS 3 [Liangliang]
Lowe, Distinctive image features from scale-invariant keypoints, IJCV 2004 (pdf)

Check the ECCV 2012 Tutorial on Modern Features
Feb 13
No class due to the winter storm
Feb 20
CLASS 4 - Mid-level Feature Coding and Pooling [Liangliang]
SLIDES CLASS 4 [Liangliang]
Lin et al, Large-scale Image Classification: Fast Feature Extraction and SVM Training, CVPR 2011 (pdf)

Chatfield et al, The devil is in the details: an evaluation of recent feature encoding methods, BMVC 2011 (pdf)
Feb 27
CLASS 5 - Encoding Structure: Part-based Models [Rogerio]
SLIDES CLASS 5 [Rogerio]
Felzenszwalb et al, A Discriminatively Trained, Multiscale, Deformable Part Model, CVPR 1998(pdf, Extended TPAMI 2010)

Check the ICCV 2013 Tutorial on Part-based Models for Recognition
Mar 06
CLASS 6 - Attributes and Semantic Features [Rogerio]
SLIDES CLASS 6 [Rogerio]
Lampert et al, Attribute-Based Classification for Zero-Shot Learning of Object Categories, TPAMI 2013 (pdf)

Check the CVPR 2013 Tutorial on Attributes
 Part II : Tools for Large-scale Image Classification and Retrieval
Mar 13
CLASS 7 - Large-scale Visual Recognition [Liangliang]
SLIDES CLASS 7 [Liangliang]
LeCun et al, Gradient-based learning applied to document recognition, 1998 (pdf)

Krizhevsky et al, ImageNet Classification with Deep Convolutional Neural Networks, NIPS 2012 (pdf)
 Spring Recess (Mar 17 – Mar 21)
Mar 27
CLASS 8 - Visual Similarity Based Image Search and Retrieval [Jun]
Zhou et al, Ranking on data manifolds, NIPS 2003 (pdf)

Davis et al, Information-theoretic metric learning, ICML 2007 (pdf)
Apr 03
CLASS 9 - Smart Indexing via Learning Based Hashing [Jun]
Weiss et al, Spectral hashing, NIPS 2008 (pdf)

Kulis and Grauman, Kernelized locality-sensitive hashing for scalable image search, ICCV 2009 (pdf)
Apr 10
CLASS 10 - Active Learning for Efficient Image Retrieval and Classification [Jun]
Jain et al, Hashing hyperplane queries to near points with applications to large-scale active learning, NIPS 2010 (pdf)

Liu et al, Compact hyperplane hashing with bilinear functions, ICML 2012 (pdf)
 Part III: Case Studies
Apr 17
CLASS 11 - Case Study: IBM Smart Surveillance Solution [Rogerio]
SLIDES CLASS 11 [Rogerio]
Feris et al, Large-Scale Vehicle Detection, Indexing, and Search in Urban Surveillance Videos, TMM 2012 (pdf)

Benenson et al, Pedestrian detection at 100 frames per second, CVPR 2012 (pdf)
Apr 24
CLASS 12 - Case Study: IBM Multimedia Analysis and Retrieval System [Liangliang]
demo page
Cao et al, Scene Aligned Pooling for Complex Video Recognition, ECCV 2012 (pdf)

Yan et al, Model-Shared Subspace Boosting for Multi-label Classification, KDD 2007 (pdf)
May 01
Reserved for student paper presentations
May 08
Final Project Presentations:

Flower Recognition: Feature Analysis and Fusion [Shun-Xuan Wang and Wenqian Liu] (best results to date on the Oxford Flowers Dataset)

Automated Axon Segmentation Using Spatio-Temporal Independent Component Analysis
[John Bowler and Mo Zhou]

Identifying Animals in the Wild [Chia Kang Chao and Yen‐Cheng Chou]

From ImageNet to Serengeti: Recognizing Animals in Wild Scenes [Guangnan Ye and Maja Rudolph]

Recognition of Animal Skin Texture Attributes in the Wild [Amey Dharwadker and Kai Zhang]

Safer Driving through Gesture Control [Kartik Darapuneni, Shuheng Gong, and Jianze Wang]