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Kuchinsky, Allan; Pering, Celine; Creech, Michael; Freeze, Dennis; Serra, Bill; Gwizdka, Jacek

doi:10.1145/302979.303143

Cited by 146 publications

(13 citation statements)

References 9 publications

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“…The concept of automatic labelling of photos has a great influence in fields of face recognition and object detection (Cui et al, 2007). Ultimately users can verbally annotate photographs or record the accompanying audio (Kuchinsky et al, 1999). It is noteworthy that most of the developed systems have not been evaluated in terms of the difficulty of PIM evaluations (Elsweiler and Ruthven, 2007) and hence the problems remain unsolved that may affect the refinding of information in general and photographs in particular.…”

Section: Why Personal Photographsmentioning

confidence: 99%

Factors in Re-Finding the Personal Photographs: Review and Possible Research Directions

Nasar¹,

Mohd²,

Ali³

2014

RJASET

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Factors effecting re-find personal photographs are often difficult to define, given its inexpressible numbers. Literature review highlights the role of human behaviors in personal photographs lifecycle such as capturing, keeping, managing and re-finding personal photographs exaggeratedly without any progress to handle all factors and so forth. Moreover, personal photographs management systems are becoming widespread, which can help people to rapidly re-find their photographs that have been seen before. Yet some research gaps remain in these systems. This study aims to clarify most possible factors, which could influence re-finding personal photographs as with strengths and weaknesses points in existing photographs management systems. It also provides propose directions for future research in this domain. A review of existing studies highlights some gaps in the literature on the role of personal photographs lifecycle, which is followed by questions for future research. Given the richness of personal photographs re-finding domain, the authors believe that the proposed questions offer avenues for scholars to explore and develop greater understanding of the role of personal photographs lifecycle in difficulty of re-finding personal photographs. The authors acknowledge that there are certain limitations to this study, namely, focusing on the review of personal photographs and not on other forms of personal information. The review presents the role of personal photographs lifecycle and its use in the context of re-finding personal photographs. Finally, this study proposes only future research directions that are far from being exhaustive, rather than presenting experimental study results. Reviewing the current literature uncovers a number of gaps regarding the difficulty of re-finding personal photographs.

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Section: Why Personal Photographsmentioning

confidence: 99%

Factors in Re-Finding the Personal Photographs: Review and Possible Research Directions

Nasar¹,

Mohd²,

Ali³

2014

RJASET

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“…This leads to more and more personal digital photos being shared online for browsing and retrieval. As collections grow rapidly, so does the demand for searching, browsing and organising of digital photos (Kuchinsky et al , 1999). Therefore, it is necessary to organise these digital photos effectively.…”

Section: Introductionmentioning

confidence: 99%

Personal photo browsing and retrieval by clustering techniques

Lin

Tsai

Roan

2008

Online Information Review

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PurposeBecause of the popularity of digital cameras, the number of personal photographs is increasing rapidly. In general, people manage their photos by date, subject, participants, etc. for future browsing and searching. However, it is difficult and/or takes time to retrieve desired photos from a large number of photographs based on the general personal photo management strategy. In this paper the authors aim to propose a systematic solution to effectively organising and browsing personal photos.Design/methodology/approachIn their system the authors apply the concept of content‐based image retrieval (CBIR) to automatically extract visual image features of personal photos. Then three well‐known clustering techniques – k‐means, self‐organising maps and fuzzy c‐means – are used to group personal photos. Finally, the clustering results are evaluated by human subjects in terms of retrieval effectiveness and efficiency.FindingsExperimental results based on the dataset of 1,000 personal photos show that the k‐means clustering method outperforms self‐organising maps and fuzzy c‐means. That is, 12 subjects out of 30 preferred the clustering results of k‐means. In particular, most subjects agreed that larger numbers of clusters (e.g. 15 to 20) enabled more effective browsing of personal photos. For the efficiency evaluation, the clustering results using k‐means allowed subjects to search for relevant images in the least amount of time.Originality/valueCBIR is applied in many areas, but very few related works focus on personal photo browsing and retrieval. This paper examines the applicability of using CBIR and clustering techniques for browsing personal photos. In addition, the evaluation based on the effectiveness and efficiency strategies ensures the reliability of our findings.

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“…1. More relevant tags are needed: As previously explained, users do not typically label their personal images and when they do, they tend to do it in "bulk" [71]. Moreover, sometimes the tags do not describe the image contents [65].…”

Section: Discussion and Implications For Designmentioning

confidence: 99%

“…One of the main problems with these tag based search interfaces is that not all tags describe the actual content of the media [65], and therefore tags can only help find the content that has been correctly tagged. Actually, Kuchinsky et al [71] found that most of the times full collections or folders are assigned the same tags, making it hard to find specific images in the collection. This fact allows for image/video analysis techniques to enhance the search and retrieval user experience, research field that has shown great activity recently [107,36].…”

Section: Introductionmentioning

confidence: 99%

“…Google Image search). However, image search in personal repositories is still a challenging task: users do not typically label each image individually, but tend to annotate their pictures in batch or bulk mode [71], assigning the same tags to groups of images that belong to the same event or photographic session. Moreover, the tags do not necessarily describe the content of the image [65].…”

Section: Media Aesthetics Introductionmentioning

confidence: 99%

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Media aesthetics based multimedia storytelling.

Obrador Espinosa

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Since the earliest of times, humans have been interested in recording their life experiences, for future reference and for storytelling purposes. This task of recording experiences --i.e., both image and video capture-- has never before in history been as easy as it is today. This is creating a digital information overload that is becoming a great concern for the people that are trying to preserve their life experiences. As high-resolution digital still and video cameras become increasingly pervasive, unprecedented amounts of multimedia, are being downloaded to personal hard drives, and also uploaded to online social networks on a daily basis. The work presented in this dissertation is a contribution in the area of multimedia organization, as well as automatic selection of media for storytelling purposes, which eases the human task of summarizing a collection of images or videos in order to be shared with other people. As opposed to some prior art in this area, we have taken an approach in which neither user generated tags nor comments --that describe the photographs, either in their local or on-line repositories-- are taken into account, and also no user interaction with the algorithms is expected. We take an image analysis approach where both the context images --e.g. images from online social networks to which the image stories are going to be uploaded--, and the collection images --i.e., the collection of images or videos that needs to be summarized into a story--, are analyzed using image processing algorithms. This allows us to extract relevant metadata that can be used in the summarization process. Multimedia-storytellers usually follow three main steps when preparing their stories: first they choose the main story characters, the main events to describe, and finally from these media sub-groups, they choose the media based on their relevance to the story as well as based on their aesthetic value. Therefore, one of the main contributions of our work has been the design of computational models --both regression based, as well as classification based-- that correlate well with human perception of the aesthetic value of images and videos. These computational aesthetics models have been integrated into automatic selection algorithms for multimedia storytelling, which are another important contribution of our work. A human centric approach has been used in all experiments where it was feasible, and also in order to assess the final summarization results, i.e., humans are always the final judges of our algorithms, either by inspecting the aesthetic quality of the media, or by inspecting the final story generated by our algorithms. We are aware that a perfect automatically generated story summary is very hard to obtain, given the many subjective factors that play a role in such a creative process; rather, the presented approach should be seen as a first step in the storytelling creative process which removes some of the ground work that would be tedious and time consuming for the user. Overall, the main contributions of this work can be capitalized in three: (1) new media aesthetics models for both images and videos that correlate with human perception, (2) new scalable multimedia collection structures that ease the process of media summarization, and finally, (3) new media selection algorithms that are optimized for multimedia storytelling purposes.

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FotoFile

Cited by 146 publications

References 9 publications

Factors in Re-Finding the Personal Photographs: Review and Possible Research Directions

Factors in Re-Finding the Personal Photographs: Review and Possible Research Directions

Personal photo browsing and retrieval by clustering techniques

Media aesthetics based multimedia storytelling.

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