EMERGENCE OF SEMANTIC CONCEPTS IN VISUAL DATABASES (2009)
Jorma Laaksonen, Ville Viitaniemi, Markus Koskela
Content-based image retrieval (CBIR) systems can be used also for other purposes than online access to unannotated image databases. In particular, when a CBIR system is equipped with an automatic...
PicSOM Experiments in TRECVID 2008 (2009)
Markus Koskela, Mats Sjöberg, Ville Viitaniemi, Jorma Laaksonen
Our experiments in TRECVID 2008 include participation in the high-level feature extraction, automatic search, video summarization, and video copy detection tasks, using a common system framework. In...
Jorma Laaksonen, Ville Viitaniemi, Markus Koskela
In this paper, we study how well our PicSOM CBIR system is able to find prototypical image segments based on imagelevel
Viitaniemi, Ville, Laaksonen, Jorma
This report presents the results of a series of experiments where knowledge of the most relevant part of images is given as additional information to a content-based image retrieval system. The most...
100 Image analysis applications 6.1 Content-based image retrieval by self-organizing maps (2008)
Erkki Oja, Jorma Laaksonen, Jukka Iivarinen, Markus Koskela, Jussi Pakkanen, Ville Viitaniemi, ...
Content-based image retrieval (CBIR) has been a subject of intensive research effort for more than a decade now. It differs from many of its neighboring research disciplines in computer vision due to...
BROWSING AN ELECTRONIC MAIL-ORDER CATALOGUE WITH PICSOM CONTENT-BASED IMAGE RETRIEVAL SYSTEM (2008)
Ville Viitaniemi, Jorma Laaksonen
This paper describes an example case where the PicSOM general-purpose content-based image retrieval system is applied onto a task of browsing electronic mail order catalogues. The images are indexed...
PicSOM experiments in TRECVID 2008 (2008)
Koskela, Markus, Sjöberg, Mats, Viitaniemi, Ville, Laaksonen, Jorma
Our experiments in TRECVID 2008 include participation in the high-level feature extraction, automatic search, video summarization, and video copy detection tasks, using a common system framework. In...
Techniques for Image Classification, Object Detection and Object Segmentation (2008)
Viitaniemi, Ville, Laaksonen, Jorma
In this paper we document the techniques which we used to participate in the PASCAL NoE VOC Challenge 2007 image analysis performance evaluation campaign. We took part in three of the image analysis...
Markus Koskela, Mats Sjöberg, Ville Viitaniemi, Jorma Laaksonen, Philip Prentis
Our experiments in TRECVID 2007 include participation in the high-level feature extraction, search, and video summarization tasks, using a common system framework based on multiple parallel...
Viitaniemi, Ville, Sjöberg, Mats, Koskela, Markus, Laaksonen, Jorma
In this paper the problem of detecting high-level features from video shots is studied. In particular, we explore the possibility of taking advantage of temporal and interconcept co-occurrence...
Use of Image Regions in Context-Adaptive Image Classification ⋆ (2008)
Ville Viitaniemi, Jorma Laaksonen
Abstract. In this paper we describe and discuss our existing PicSOM software framework from the point of view of context-adaptive analysis of image contents, especially its method for using automatic...
Molinier, Matthieu, Viitaniemi, Ville, Koskela, Markus, Laaksonen, Jorma, Rauste, Yrjö, Lönnqvist, Anne, ...
Self-Organising Maps (SOMs) have been successfully applied to content-based image retrieval (CBIR). In this study, we investigate the potential of PicSOM, an image database browsing system, applied...
ABSTRACT Rushes Summarization with Self-Organizing Maps (2008)
Markus Koskela, Ville Viitaniemi
In this paper, we describe our approach for video summarization that was applied to the BBC rushes material as part of the TRECVID 2007 evaluations. The method consists of initial shot boundary...
Overview of the ImageCLEF 2007 Object Retrieval Task (2008)
Deselaers, Thomas, Hanbury, Allan, Viitaniemi, Ville, Farquhar, Jason D.R., Brendel, Mátyás, Daróczy, Bálint, ...
We describe the object retrieval task of ImageCLEF 2007, give an overview of the methods of the participating groups, and present and discuss the results. The task was based on the widely used PASCAL...
Techniques for image classification, object detection and object segmentation (2008)
Viitaniemi, Ville, Laaksonen, Jorma
In this paper we outline the techniques which we used to participate in the PASCAL NoE VOC Challenge 2007 image analysis performance evaluation campaign. We took part in three of the image analysis...
Experiments on Selection of Codebooks for Local Image Feature Histograms (2008)
Viitaniemi, Ville, Laaksonen, Jorma
Histograms of local features have proven to be powerful representations in image classification and object detection. In this paper we experimentally compare techniques for selecting histogram...
Improving the accuracy of global feature fusion based image categorisation (2007)
Viitaniemi, Ville, Laaksonen, Jorma
In this paper we consider the task of categorising images of the Corel collection into semantic classes. In our earlier work, we demonstrated that state-of-the-art accuracy of supervised categorising...
Empirical investigations on benchmark tasks for automatic image annotation (2007)
Viitaniemi, Ville, Laaksonen, Jorma
Automatic image annotation aims at labeling images with keywords. In this paper we investigate three annotation benchmark tasks used in literature to evaluate annotation systems' performance. We...
PicSOM experiments in TRECVID 2007 (2007)
Koskela, Markus, Sjöberg, Mats, Viitaniemi, Ville, Laaksonen, Jorma, Prentis, Philip
Our experiments in TRECVID 2007 include participation in the high-level feature extraction, search, and video summarization tasks, using a common system framework based on multiple parallel...
Rushes summarization with Self-Organizing Maps (2007)
Koskela, Markus, Sjöberg, Mats, Laaksonen, Jorma, Viitaniemi, Ville, Muurinen, Hannes
In this paper, we describe our approach for video summarization that was applied to the BBC rushes material as part of the TRECVID 2007 evaluations. The method consists of initial shot boundary...
Overview of the ImageCLEF 2007 Object Retrieval Task (2007)
Deselaers, Thomas, Hanbury, Allan, Viitaniemi, Ville, Benczur, Andras, Brendel, Matyas, Daroczy, Balint, ...
We describe the object retrieval task of ImageCLEF 2007, give an overview of the methods of the participating groups, and present and discuss the results. The task was based on the widely used PASCAL...
Thoughts on evaluation of image retrieval inspired by ImageCLEF 2007 object retrieval task (2007)
Viitaniemi, Ville, Laaksonen, Jorma
In this paper we discuss questions on information retrieval evaluation brought up by the analysis of the recent ImageCLEF 2007 object retrieval task. We question the adequacy of the pooling strategy...
Viitaniemi, Ville, Laaksonen, Jorma
In this work we consider two traditional metrics for evaluating performance in automatic image annotation, the normalised score (NS) and the precision/recall (PR) statistics, particularly in...
Viitaniemi, Ville, Laaksonen, Jorma
In this paper we consider two traditional metrics for evaluating the performance in automatic image annotation, the normalised score (NS) and the precision/recall (PR) statistics, particularly in...
Video summarization with SOMs (2007)
Laaksonen, Jorma, Koskela, Markus, Sjöberg, Mats, Viitaniemi, Ville, Muurinen, Hannes
Video summarization is a process where a long video file is converted to a considerably shorter form. The video summary can then be used to facilitate efficient searching and browsing of video files...
Video Summarization with SOMs (2007)
Laaksonen, Jorma, Koskela, Markus, Sjöberg, Mats, Viitaniemi, Ville, Muurinen, Hannes
Video summarization is a process where a long video file is converted to a considerably shorter form. The video summary can then be used to facilitate efficient searching and browsing of video files...
Overview of the ImageCLEF 2007 object retrieval task (2007)
Thomas Deselaers, Allan Hanbury, Ville Viitaniemi, András Benczúr, Mátyás Brendel, Bálint Daróczy, ...
Abstract. We describe the object retrieval task of ImageCLEF 2007, give an overview of the methods of the participating groups, and present and discuss the results. The task was based on the widely...
Use of image regions in context adaptive image classification (2006)
Viitaniemi, Ville, Laaksonen, Jorma
In this paper we describe and discuss our existing PicSOM software framework from the point of view of context-adaptive analysis of image contents, especially its method for using automatic image...
Focusing keywords to automatically extracted image segments using self-organising maps (2006)
Viitaniemi, Ville, Laaksonen, Jorma
In this chapter we consider the problem of keyword focusing. In keyword focusing the input data is a collection of images that are annotated with a given keyword, such as "car"'. The problem is to...
Emergence of ontological relations from visual data with self-organizing maps (2006)
Laaksonen, Jorma, Viitaniemi, Ville
In this paper we examine how Self-Organizing Maps (SOMs) can be used in detecting and describing emergent ontological relations between semantic objects and object classes in a visual database. The...
Techniques for still image scene classification and object detection (2006)
Viitaniemi, Ville, Laaksonen, Jorma
In this paper we consider the interaction between different semantic levels in still image scene classification and object detection problems. We present a method where a neural method is used to...
Sjöberg, Mats, Viitaniemi, Ville, Laaksonen, Jorma, Honkela, Timo
An art installation was on display in the Centre Pompidou National Museum of Modern Art in Paris, where visitors could contribute with their own personal objects, adding keyword descriptions and...
The 2005 PASCAL Visual Object Classes Challenge (2006)
Everingham, Mark, Zisserman, Andrew, Williams, Christopher, Van Gool, Luc, Allan, Moray, Bishop, Chris, ...
The PASCAL Visual Object Classes Challenge ran from February to March 2005. The goal of the challenge was to recognize objects from a number of visual object classes in realistic scenes (i.e. not...
Emergence of semantics from multimedia databases (2006)
Oja, Erkki, Sjöberg, Mats, Viitaniemi, Ville, Laaksonen, Jorma
In this book chapter we study how large multimedia databases can be understood and indexed by using the database context and relationships of the data items, in addition to the low-level data itself....
The 2005 pascal visual object classes challenge (2006)
Mark Everingham, Andrew Zisserman, Luc Van Gool, Moray Allan, Christopher M. Bishop, ...
Abstract. The PASCAL Visual Object Classes Challenge ran from February to March 2005. The goal of the challenge was to recognize objects from a number of visual object classes in realistic scenes...
Emergence of ontological relations from visual data with self-organizing maps (2006)
Jorma Laaksonen, Ville Viitaniemi
In this paper we examine how Self-Organizing Maps (SOMs) can be used in detecting and describing emergent ontological relations between semantic objects and object classes in a visual database. The...
Ville Viitaniemi, Jorma Laaksonen
the input data is a collection of images that are annotated with a given keyword, such as “car”. The problem is to attribute the annotation to specific parts of the images. There exists plenty of...
The 2005 pascal visual object classes challenge (2006)
Mark Everingham, Andrew Zisserman, Luc Van Gool, Moray Allan, Christopher M. Bishop, ...
Abstract. The PASCAL Visual Object Classes Challenge ran from February to March 2005. The goal of the challenge was to recognize objects from a number of visual object classes in realistic scenes...
The 2005 pascal visual object classes challenge (2006)
Mark Everingham, Andrew Zisserman, Luc Van Gool, Moray Allan, Christopher M. Bishop, ...
Abstract. The PASCAL Visual Object Classes Challenge ran from February to March 2005. The goal of the challenge was to recognize objects from a number of visual object classes in realistic scenes...
Keyword-detection approach to automatic image annotation (2005)
Viitaniemi, Ville, Laaksonen, Jorma
In this paper we consider the problem of automatically annotating images with keywords. We first discuss performance measures for the problem in some length. We propose a new information-theory based...
Laaksonen, Jorma, Viitaniemi, Ville, Koskela, Markus
In this paper, we study how well our PicSOM CBIR system is able to find prototypical image segments based on image-level keywords and automatic image segmentation. We also study different methods for...
Emergence of semantic concepts in visual databases (2005)
Laaksonen, Jorma, Viitaniemi, Ville, Koskela, Markus
Content-based image retrieval (CBIR) systems can be used also for other purposes than online access to unannotated image databases. In particular, when a CBIR system is equipped with an automatic...