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Handheld mobile devices referring to mobile phones and tablets become the major output medium for augmented reality (AR), which have seen significant growth in popularity and usage among the public due to the growing release of consumer-oriented communication products nowadays, especially touchscreen smartphones. Unlike traditional desktop or tabletop AR (large display-based) and head-mounted display-based AR systems, small display-based AR (handheld mobile display) requires different interaction techniques that mostly utilize single-hand interaction as well as the limitation of small screen display and limited activity time due to the battery operation hour of handheld mobile devices. However, in handheld mobile AR, research is still lacking, especially research that focuses on 3D interaction in handheld mobile AR for virtual object manipulation. Thus, this paper provides an overview of 3D interaction techniques in handheld mobile AR with critical analysis. First, we describe three main interaction technique categories that applicable in handheld mobile AR, which is touch-based interaction, mid-air gestures-based interaction, and device-based interaction techniques, of their basic concepts on 3D object manipulation. Then, we classify and systematize the highlighted techniques and discuss the advantages and drawbacks of each. Previous studies for widely used techniques have been studied comprehensively. We then draw up a comparison among the different techniques based on the important elements considered in handheld mobile AR. The aim of this paper is to provide researchers with background information on AR and those who are interested in the field of 3D interaction, realizing each technique category. INDEX TERMS 3D object manipulation, device-based interaction technique, mid-air gestures-based interaction technique, handheld mobile AR, touch-based interaction technique. I. INTRODUCTIONAccording to Milgram and Kishino [1], augmented reality (AR) refers to all cases in which the display of an otherwise real environment is augmented by means of virtual (computer graphic) objects. Extended from this definition, Azuma [2] defined that AR is the variation of virtual environments or virtual reality; however, unlike virtual reality that immerses a user inside a synthetic environment and the user cannot see the real world around him/her, AR allows the user to see the real world, with virtual objects composited with the real world. Beyond that, some researchers have doneThe associate editor coordinating the review of this manuscript and approving it for publication was Waleed Alsabhan. a number of surveys or reviews about AR. For example, Krevelen and Poelman [3], drawing up conclusions from several previous works, defined the AR system as: 1) combining real and virtual objects in a real environment; 2) registering real and virtual objects with each other and 3) running interactively, in 3D and in real-time. From another point of view, Mekni and Lemieux [4] proposed to define AR as systems that have the following charact...

This survey provides an overview of popular pathfinding algorithms and techniques based on graph generation problems. We focus on recent developments and improvements in existing techniques and examine their impact on robotics and the video games industry. We have categorized pathfinding algorithms based on a 2D/3D environment search. The aim of this paper is to provide researchers with a thorough background on the progress made in the last 10 years in this field, summarize the principal techniques, and describe their results. We also give our expectations for future trends in this field and discuss the possibility of using pathfinding techniques in more extensive areas.

This paper presents a review of user expectation towards Augmented Reality (AR) and the acceptance of AR for technologyenhanced teaching and learning. Augmented Reality is a technology that superimposes a computer-generated image over a user's view of the real world, thus providing a composite view. This technology has been used in many fields such as marketing, military, entertainment and many other sectors. Studies have found that AR technology can enhance teaching and learning, however more research still needs to be conducted about the acceptance of AR as a learning tool and what users in education expect from the technology. An understanding of the user expectation is one of the key foundations towards establishing better-designed AR systems and applications that will result in more acceptance of this technology. To help with this, this paper reviews previous research on user expectations of AR in education and its acceptance.

Over the past decade, enhanced computing capabilities and mobile technologies have begotten the upsurge of innovative mobile health (mHealth) solutions, and many research efforts have occurred recently in the area of technology-based interventions (TBI) for autism spectrum disorders (ASD). Mobile augmented reality (MAR) refers to AR systems that use the handheld mobile device medium (mobile phones, tablets or smart glasses). This article reports the results of a systematic review undertaken on the use of MAR for ASD-related skills learning from the year 2010. It aims to provide an insight into the current state of research on MAR interventions and to provide guidance to relevant designers and researchers. We searched seven databases and retrieved 625 articles initially. After exclusion and screening, 36 articles were reviewed reporting on using MAR to improve various skills of children and adolescents with ASD, and 10 research questions related to PICO (P: Population, I: Intervention, C: Comparison, O: Outcomes) were addressed. This study identifies challenges that still exist in the research efforts towards the development of applications exploiting the MAR for ASD interventions: technology issues, research design consideration, subjective assessment etc. The studies examined suggest researchers should focus on users and improve the quality of the MAR app. In addition, more effective research methods and evaluation methods could be involved in future studies to facilitate the development of MAR intervention applications.

Content Based Image Retrieval (CBIR) is a technique that enables a user to extract an image based on a query, from a database containing a large amount of images. A very fundamental issue in designing a content based image retrieval system is to select the image features that best represent the image contents in a database. In this paper, our proposed method mainly concentrated on database classification and efficient image representation. We present a method for content based image retrieval based on support vector machine classifier. In this method the feature extraction was done based on the colour string coding and string comparison. We succeed in transferring the images retrieval problem to strings comparison. Thus the computational complexity is decreases obviously. The image database used in our experiment contains 1800 colour images from Corel photo galleries. This CBIR approach has significantly increased the accuracy in obtaining results for image retrieval. © 2015 The Authors. Published by Elsevier B.V. Peer-review under responsibility of scientific committee of 2nd International Symposium on Big Data and Cloud Computing (ISBCC'15).

Interaction for Handheld Augmented Reality (HAR) is a challenging research topic because of the small screen display and limited input options. Although 2D touch screen input is widely used, 3D gesture interaction is a suggested alternative input method. Recent 3D gesture interaction research mainly focuses on using RGB-Depth cameras to detect the spatial position and pose of fingers, using this data for virtual object manipulations in the AR scene. In this paper we review previous 3D gesture research on handheld interaction metaphors for HAR. We present their novelties as well as limitations, and discuss future research directions of 3D gesture interaction for HAR. Our results indicate that 3D gesture input on HAR is a potential interaction method for assisting a user in many tasks such as in education, urban simulation and 3D games.