NDLI: Biologically plausible detection of amorphous objects in the wild

Content Provider	IEEE Xplore Digital Library
Author	Sunhyoung Han Vasconcelos, N.
Copyright Year	2011
Description	Author affiliation: Department of Electrical and Computer Engineering, University of California, San Diego (Sunhyoung Han; Vasconcelos, N.)
Abstract	The problem of amorphous object detection is investigated. A dataset of amorphous objects, Panda bears, with no defined shape or distinctive edge configurations is introduced. A biologically plausible amorphous object detector, based on discriminant saliency templates, is then proposed. The detector is based on the principles of discriminant saliency, and implemented with a hierarchical architecture of two layers. The first computes a feature-based top-down saliency measure tuned for object detection. The second relies on a similar saliency measure, but based on saliency templates, selected from the responses of the first layer. This architecture is shown to have a number of interesting properties for amorphous object detection, including the ability to detect objects characterized by the absence of features, and an interpretation as discriminant blob detection. Extensive experimental evaluation shows that it substantially outperforms state-of-the-art approaches for non-amorphous object detection, such as deformable parts models, sparse coded pyramid matching, detection based on the bag-of-features architecture, and the Viola and Jones approach. This brings into question some currently popular beliefs about object detection, which are discussed.
Starting Page	24
Ending Page	31
File Size	2525701
Page Count	8
File Format	PDF
ISBN	9781457705298
ISSN	21607516
e-ISBN	9781457705304
DOI	10.1109/CVPRW.2011.5981770
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-06-20
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Training Visualization Shape Image edge detection Detectors Object detection Feature extraction
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Object Detection Using Principal Contour Fragments

Description and tracking of moving articulated objects

Biologically Plausible Detection of Amorphous Objects (2011)

Efficient region search for object detection

Feature Pairs Connected by Lines for Object Recognition

Human visual system inspired object detection and recognition

Shape detector for generic ball detection

Object detection based on local feature matching and segmentation

Shape feature extraction from object corners

Biologically plausible detection of amorphous objects in the wild

Similar Documents

Object Detection Using Principal Contour Fragments

Description and tracking of moving articulated objects

Biologically Plausible Detection of Amorphous Objects (2011)

Efficient region search for object detection

Feature Pairs Connected by Lines for Object Recognition

Human visual system inspired object detection and recognition

Shape detector for generic ball detection

Object detection based on local feature matching and segmentation

Shape feature extraction from object corners

Biologically plausible detection of amorphous objects in the wild