The growth of inbound travel is fully coordinate with the successful urban development. Increasing the number of inbound travelers not only creates more jobs and economic opportunities but also drives the country toward prosperity. Thus, inbound traveler analysis through trajectory pattern mining, a subfield of urban computing, is regarded as a promising solution. This paper introduces large-scale mobile ad requests as an alternative data source of trajectory pattern mining in order to eliminate the limitations of conventional data sources, such as GPS data, cellular data, and IP address data. In addition, to expedite a comprehensive inbound traveler analysis, we build TraVis, a real-world system for efficiently exploring the inbound travelers' activities through the interactive visualization interface. By incorporating various modules, such as mobile users' home country and travel intent prediction, frequent trajectory pattern mining, and interactive visualization, TraVis proves the capability of profiling the travelers' behavior pattern. We use Japan inbound travelers in the case study to present the mining insights, and we also demonstrate the extensive system functionalities. Our system has been assisting Japan government agencies to formulate travel marketing strategies, including tourist experience enhancement and attractions marketing.

Google Maps with Street View (GSV) provides ways to explore the world but it lacks efficient ways to present a journey. Hyperlapse provides another ways for quick glimpsing the street-views along the route; however, its viewing experience is also not comfortable and could be tedious when the route is long-distance. In this paper, we provide an efficient and enjoyable way to present street view sequences of long journey. Street view journey video accompanied with locally listened music will be produced by the proposed approach. During the move between locations, we use the speed control techniques for animation production to improve the viewing experience. User evaluation results show that the proposed method increases the satisfaction of users in viewing the street view sequences.

In this work, a low-cost and efficient system is proposed to automatically analyze the halfpipe (HP) sports videos. In addition to the court color ratio information, we find the player region by using salient object detection mechanisms to face the challenge of motion blurred scenes in HP videos. Besides, a novel and efficient method for detecting the spin event is proposed on the basis of native motion vectors existing in a compressed video. Experimental results show that the proposed system is effective in recognizing the hard-to-be-detected spin events in HP videos.

This paper proposes an indexing and teaching focus mining system for lecture videos recorded in an unconstraint environment. The slide structure can be reconstructed by an edge-based shot change detection algorithm. Besides, the teaching focus can be extracted according to instructor’s behavior, including the gesture, the lecture time for each slide, and the speech speed. Experiment results show the feasibility of the proposed method, that is, the slide shots can be correctly detected even if the illumination conditions is variant or the slides are obstructed by the instructor or students, and the teaching focus can be well extracted to provide learners an efficient way to study.

This demonstration presents an innovative framework for virtual content insertion in an interactive way. The virtual content is inserted into video with evolved animations according to predefined behaviors, and generates interactions with video contents. In order to reduce the intrusiveness and improve the impression for viewers, the evolution process is divided into distinct yet dependent phases, in which the virtual content evolves its appearances and behaviors according to the incremental interactions. Therefore, the augmented videos generated by the proposed system establish visually relevant connection between the inserted virtual content and the source videos, and increase the acceptability and the attractiveness at the same time. Moreover, the proposed system enables video owners to create entertaining personalized videos effectively, and engages viewers with the storyline.

With the constraint of limited intrusiveness, maximizing the advertising efficiency in sports video has been known as a challenging problem. In this paper, we propose a virtual advertisement system with novel advertising strategy, called Virtual Spotlighted Advertising (ViSA), for broadcasting tennis videos. We take psychology, advertising theory, and computational aesthetics into account for improving the effectiveness of advertising. ViSA system automatically detects the candidate insertion points in both temporal and spatial domains and estimates the maximum effective region for message communication. Then, the harmonically re-colored advertisements with foveation model based non-uniform transparency, are projected on the court in tennis videos. The experiments and evaluation results showed the effectiveness of ViSA, for sports video advertising, in terms of recall and recognition.

Nowadays, travel has become a popular activity for people to relax their body and mind. Taking photos is then often an inevitable and frequent event during one's trip for recording the enjoyable experience. To help people to relive the wonderful travel experience they had recorded in photos, this paper presents a system, Photo Navigator, for enhancing the photo browsing experience by creating a new browsing style with a realistic feel to users as being into the scenes and taking a trip back in time to revisit the place. The proposed system is characterized by two main features. First, it better reveals the spatial relations among photos and offers a strong sense of space by taking users to fly into the scenes. Second, it is fully automatic and makes plausible for novice users to utilize the 3D technologies that are traditionally complex to manipulate. The proposed system is compared with two other photo browsing tools, ACDSee's photo slideshow and Microsoft's PhotoStory. User studies show that people would comparatively favor the browsing style we offer and appreciate the ease to create such a style.