Object identification and retrieval from efficient image matching. Snap2Tell with the STOIC dataset

Chevallet, Jean–Pierre; Lim, Joo‐Hwee; Leong, Mun-Kew

doi:10.1016/j.ipm.2006.07.017

Cited by 13 publications

(8 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A mobile landmark recognition system called Snap2Tell was developed in Chevallet et al [2007]. However, the authors use a simple matching technique based on color histograms and a 1NN classifier, combined with localization information.…”

Section: Related Workmentioning

confidence: 99%

Fast Image Classification for Monument Recognition

Amato

Falchi

Gennaro

2015

J. Comput. Cult. Herit.

View full text Add to dashboard Cite

Content-based image classification is a wide research field that addresses the landmark recognition problem. Among the many classification techniques proposed, the k-nearest neighbor (kNN) is one of the most simple and widely used methods. In this article, we use kNN classification and landmark recognition techniques to address the problem of monument recognition in images. We propose two novel approaches that exploit kNN classification technique in conjunction with local visual descriptors.The first approach is based on a relaxed definition of the local feature based image to image similarity and allows standard kNN classification to be efficiently executed with the support of access methods for similarity search.The second approach uses kNN classification to classify local features rather than images. An image is classified evaluating the consensus among the classification of its local features. In this case, access methods for similarity search can be used to make the classification approach efficient.The proposed strategies were extensively tested and compared against other state-of-the-art alternatives in a monument and cultural heritage landmark recognition setting. The results proved the superiority of our approaches.An additional relevant contribution of this work is the exhaustive comparison of various types of local features and image matching solutions for recognition of monuments and cultural heritage related landmarks.

show abstract

Section: Related Workmentioning

confidence: 99%

Fast Image Classification for Monument Recognition

Amato

Falchi

Gennaro

2015

J. Comput. Cult. Herit.

View full text Add to dashboard Cite

show abstract

“…Hence, a detection is required for many services. Content based image retrieval may be used for this purpose [7]. We have not implemented it.…”

Section: Resource Optimization For Content Deliverymentioning

confidence: 99%

MediaServ: Resource optimization in subscription based media crowdsourcing

Rizvi

Ahmed

Bashir

et al. 2015

2015 International Conference on Networking Systems and Security (NSysS)

View full text Add to dashboard Cite

show abstract

“…OVERVIEW OF MOBILE LANDMARK RECOGNITION FOR INFORMATION RETRIEVAL Many mobile landmark recognition systems have been developed in recent years [8], [13]- [17], [26], [34]- [37]. Most of the existing systems utilize content analysis and concept classification techniques for recognition [8], [13]- [17], [26].…”

Section: IImentioning

confidence: 99%

“…Most of the existing systems utilize content analysis and concept classification techniques for recognition [8], [13]- [17], [26]. Some recent works have used context information to assist in landmark recognition [34]- [37]. The eye-Phone [34], an invention by SuperWise Technologies AG, was designed as a tourist information guide.…”

Section: IImentioning

confidence: 99%

See 1 more Smart Citation

A Survey on Mobile Landmark Recognition for Information Retrieval

Chen

Yap

et al. 2009

2009 Tenth International Conference on Mobile Data Management: Systems, Services and Middleware

View full text Add to dashboard Cite

The growing usage of mobile devices has led to proliferation of many mobile applications. A growing trend in mobile applications is centered on mobile landmark recognition. It is a new mobile application that recognizes a captured landmark using the mobile device and retrieves related information. This paper will present a survey on mobile landmark recognition for information retrieval. A general overview of existing mobile landmark recognition systems will be summarized. The techniques and algorithms used in the literatures, including content analysis of landmarks and classification methods for recognition, will be described.

show abstract

Object identification and retrieval from efficient image matching. Snap2Tell with the STOIC dataset

Cited by 13 publications

References 5 publications

Fast Image Classification for Monument Recognition

Fast Image Classification for Monument Recognition

MediaServ: Resource optimization in subscription based media crowdsourcing

A Survey on Mobile Landmark Recognition for Information Retrieval

Contact Info

Product

Resources

About