2016 24th Mediterranean Conference on Control and Automation (MED) 2016
DOI: 10.1109/med.2016.7535987
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Abstract: This paper presents an interdisciplinary study joining insights of landscape architecture and computer vision. In this work we used a dataset of contemplative landscape images that was collected and evaluated by experts in landscape architecture. We used the dataset to develop nine kmeans clustering and one K-nearest neighbors models that are able to score landscape images based on seven different landscape image features (layers, landform, vegetation, color and light, compatibility, archetypal elements, chara… Show more

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Cited by 4 publications
(7 citation statements)
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“…Further studies, focusing on people's mobility through a landscape, can address the hypothesis of the mental health benefits of VLC. In order to extend the knowledge of landscape imageability attributes (e.g., landscape layers, color and light, adjacent scenery, visible archetypal elements, landmarks), the artificial expert evaluation tool [115] can be used.…”
Section: Discussionmentioning
confidence: 99%
“…Further studies, focusing on people's mobility through a landscape, can address the hypothesis of the mental health benefits of VLC. In order to extend the knowledge of landscape imageability attributes (e.g., landscape layers, color and light, adjacent scenery, visible archetypal elements, landmarks), the artificial expert evaluation tool [115] can be used.…”
Section: Discussionmentioning
confidence: 99%
“…An operationalized concept of CLM can serve as the basis for creating digital image processing tools that can help evaluate large datasets of photos. Such research is currently underway, for example the prototype of the Contemplative Landscape Automated Scoring System (CLASS), an artificial intelligence client, instantly scores any given digital image of a landscape according to the CLM features with an accuracy comparable to that of a trained expert [50]. There are also emerging automated approaches into landscape imageability focusing of extracting the smallest number of possible viewpoints [51].…”
Section: Summary Of Findings Contributions and Limitations Of The Studymentioning
confidence: 99%
“…In the walking route, the landscape (such as sky, trees, and landmarks) and facilities (such as railings, seats, and streetlights) can improve the pedestrian walking experience [27]. The more identifying tag elements, the more image elements there are suitable for walking.…”
Section: Image Elements Of Street View Photomentioning
confidence: 99%
“…improve the pedestrian walking experience [27]. The more identifying tag elements, the more image elements there are suitable for walking.…”
Section: Service Capacity and Pedestrian Environment At Park Levelmentioning
confidence: 99%
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