'Color histogram' presentation slideshows

Image Retrieval by Content (CBIR)

2.52k views • 78 slides

Color and Texture Ch 6 and 7 of Shapiro

Color and Texture Ch 6 and 7 of Shapiro. How do we quantify them? How do we use them to segment an image?. Color (Summary). Used heavily in human vision Color is a pixel property, making some recognition problems easy Visible spectrum for humans is 400 nm (blue) to 700 nm (red)

967 views • 75 slides

Lecture 2

Lecture 2. Mei-Chen Yeh 03/09/2010. Outline. Demos Image representation and feature extraction Global features Local features: SIFT Assignment #2 (due: 03/16). Demos. Augmented Reality http://www.youtube.com/watch?v=P9KPJlA5yds http://www.youtube.com/watch?v=U2uH-jrsSxs Tracking

714 views • 62 slides

Gary Bradski, Intel, Stanford CAs: Dan Maynes-Aminzade, Mitul Saha, Greg Corrado

761 views • 61 slides

Image Categorization

03/15/11. Image Categorization. Computer Vision CS 543 / ECE 549 University of Illinois Derek Hoiem. Thanks for feedback HW 3 is out Project guidelines are out. Last classes. Object recognition: localizing an object instance in an image

731 views • 60 slides

Image and Video Retrieval

Image and Video Retrieval LBSC 796/INFM 718R Session 13, December 3, 2007 Douglas W. Oard Agenda Questions Image retrieval Video retrieval Finishing up Speech and Music Project presentations Image Retrieval We have already discussed three approaches Controlled vocabulary indexing

905 views • 49 slides

Image and Video Retrieval

Image and Video Retrieval. LBSC 796/INFM 718R Session 13, May 4, 2011 Douglas W. Oard. Agenda. Questions Image retrieval Video retrieval Finishing up Speech and Music Project presentations. Image Retrieval. We have already discussed three approaches Controlled vocabulary indexing

696 views • 49 slides

Computer Vision, Part 1

660 views • 48 slides

RETRIEVAL OF MULTIMEDIA OBJECTS USING COLOR SEGMENTATION AND DIMENSION REDUCTION OF FEATURES

RETRIEVAL OF MULTIMEDIA OBJECTS USING COLOR SEGMENTATION AND DIMENSION REDUCTION OF FEATURES. Mingming Lu, Qiyu Zhang, Wei-Hung Cheng, Cheng-Chang Lu Department of Computer Science Kent State University. Data Mining and Knowledge Management. Processing multimedia objects

543 views • 43 slides

Color

562 views • 42 slides

Image Retrieval: Current Techniques, Promising Directions, and Open Issues

Image Retrieval: Current Techniques, Promising Directions, and Open Issues. Yong Rui, Thomas Huang and Shih-Fu Chang Published in the Journal of Visual Communication and Image Representation. Presented by: Deepak Bote. Presentation Outline. History of image retrieval – Issues faced

592 views • 41 slides

Image indexing and retrieving using histogram based methods

Image indexing and retrieving using histogram based methods. 03/7/15 資工研所 陳慶鋒. Outline. Histogram based methods Image retrieval using the three methods Experimental result Library of Image formats Future work References. Histogram based features. Color Histogram Histogram Refinement

459 views • 32 slides

434 views • 32 slides

Color: Readings: Ch 6: 6.1-6.5

Color: Readings: Ch 6: 6.1-6.5. color spaces color histograms color segmentation. Some Properties of Color. Color is used heavily in human vision. Color is a pixel property, that can make some recognition problems easy.

529 views • 26 slides

Street-to-Shop: Cross-Scenario Clothing Retrieval via Parts Alignment and Auxiliary Set

Street-to-Shop: Cross-Scenario Clothing Retrieval via Parts Alignment and Auxiliary Set. Si Liu+, Zheng Song, Guangcan Liu , Changsheng Xu +, Hanqing Lu+, Shuicheng Yan* * ECE Department, National University of Singapore + NLPR, Institute of Automation, Chinese Academy of Science.

368 views • 20 slides

Move and the Robot will Learn: Vision-based Autonomous Learning of Object Models

Move and the Robot will Learn: Vision-based Autonomous Learning of Object Models. Xiang L i and Mohan Sridharan Stochastic Estimation and Autonomous Robotics Lab (SEARL) Department of Computer Science Texas Tech University Nov 27 , 2013. Object Recognition on Robots. Challenges:

349 views • 19 slides

Foreign Body Detection in Ear Under the guidance of : Dr. Phalguni Gupta Mr. Aaditya Nigam

Foreign Body Detection in Ear Under the guidance of : Dr. Phalguni Gupta Mr. Aaditya Nigam. Abhra Dasgupta (13111003) Muktinath Vishwakarma (13111034). Problem Statement. Given an image of an ear we are to detect the presence of a foreign body(e.g.: ear-ring) if present. Literary Survey.

378 views • 19 slides

Modeling Spatial-Chromatic Distribution for CBIR

Modeling Spatial-Chromatic Distribution for CBIR. NTUT CSIE D.W. Lin 2004.3.19. Outlines. Review Incorporating shape into color information Geometry enhanced color histogram Modeling spatial-chromatic distribution Nakagami-m distribution Refining the modeling efficiency

360 views • 19 slides

Chapter 11

Chapter 11. Beyond Bag of Words. Question Answering. Providing answers instead of ranked lists of documents Older QA systems generated answers Current QA systems extract answers from large corpora such as the Web

380 views • 15 slides

Computational Agriculture: Video Monitoring of Honey Bees

Computational Agriculture: Video Monitoring of Honey Bees. Subhabrata Bhattacharya (University of Central Florida) , Lily Mummert, Jason Campbell, and Rahul Sukthankar (Intel Labs Pittsburgh). Video Monitoring/Challenges. Why honey bees?. Detection/Tracking Dataflow. Non-disruptive

272 views • 1 slides