Wednesday, August 27, 2014


This is an example implementation of Golden Retriever - an open source Image Retrieval Engine, located at

You may use this source for building a command line based image search engine.

Example command line arguments.

Adding an imagefolder

java -jar ajmg6.jar create ImagePoolName /home/username/YourGrireDb/db /home/username/YourImageFilesFolder 1f multi

Searching for an Image

java -jar ajmg6.jar search ImagePoolName /home/username/YourGrireDb/db /home/username/YourSourceFile.jpg

Tuesday, August 5, 2014

Click’n’Cut: Crowdsourced Interactive Segmentation with Object Candidates

Carlier A, Salvador A, Giró-i-Nieto X, Marques O, Charvillat V. Click’n’Cut: Crowdsourced Interactive Segmentation with Object Candidates. In: 3rd International ACM Workshop on Crowdsourcing for Multimedia (CrowdMM). In Press


This paper introduces Click’n’Cut, a novel web tool for in- teractive object segmentation addressed to crowdsourcing tasks. Click’n’Cut combines bounding boxes and clicks gen- erated by workers to obtain accurate object segmentations. These segmentations are created by combining precomputed object candidates in a light computational fashion that al- lows an immediate response from the interface. Click’n’Cut has been tested with a crowdsourcing campaign to anno- tate a subset of the Berkeley Segmentation Dataset (BSDS). Results show competitive results with state of the art, es- pecially in time to converge to a high quality segmentation. The data collection campaign included golden standard tests to detect cheaters.