This article proposes a framework for creating user-preference-aware music medleys from users' music collections. We treat the medley generation process as an audio version of a musical dice game. Once the user's collection has been analyzed, the system is able to generate various pleasing medleys. This flexibility allows users to create medleys according to the specified conditions, such as the medley structure or the must-use clips. Even users without musical knowledge can compose medley songs from their favorite tracks. The effectiveness of the system has been evaluated through both objective and subjective experiments on individual components in the system.

3D HEVC is one of the extensions of HEVC (High Efficiency Video Coding), which is the latest video coding standard developed by the Joint Collaborative Team on Video Coding (JCT-VC). The inherent high computing complexity of 3D HEVC handicaps its usage in practical applications. HEVC replaces the macroblock (MB) of H.264 with the largest coding unit (LCU), in which coding units (CUs) of sizes 64 × 64, 32 × 32, 16 × 16, or 8 × 8 pixels are used to build a coding tree unit (CTU). HEVC encoder will traverse the coding modes from the root (the coding level is 0) to the leaves (the coding level is 3) of the CTU. As a result, how to accelerate the encoding process of 3D HEVC with negligible loss of coding efficiency is a hot research topic in the field of video coding. Figure 1 shows the coding level distributions of I04 and I14, where Ikj represents the j-th frame in the k-th GOP. The POC's (picture order counts) of the two frame are P(I04) = 4 and P(I14) = 12 when GOP size is 8. From Figure 1 we observed that, in B-slices, the distributions of "optimal coding level = zero" for adjacent GOP's are almost the same. We found that the required coding level will be similar when the two CUs have similar depth values. We utilize this correlation to limit the required coding level visiting of a given CU which accelerates the encoding process. In this paper, a fast mode decision algorithm for 3D HEVC, based on the depth information related coding mode similarity, is proposed. According to the experimental results, the proposed algorithm can reduce up to 72% executing time of the overall encoding process, while the loss in coding efficiency is negligible.

The prevalence of digital technologies allows people to easily create and share their own media contents, but sometimes we do not have handy tools to manipulate the media we want to create. For example, while creating personal films, a user may separately find the music segment that matches each part of the video, and then concatenate the segments to create the soundtrack that matches the visual contents along the timeline. However, one may lose the temporal coherence between consecutive music segments if the user just choose music segments that best match parts of the video contents. In this study, we focus on how to smoothly connect not-so-coherent music clips and make the transition natural and pleasant to hear. In particular, we improve the temporal smoothness by bar alignment and dual tempo adjustment. To further fit in with the transition between clips, we incorporate "sound effect insertion" which is a commonly used technique in popular song composition/remixing. In order to provide pleasant listening experience and systematically analyze the effectiveness of the proposed music bridging method, we have conducted specifically designed experiments to collect subjective opinions and reduce the cognitive loads of the participants. The experimental results indicate that with proper arrangement for creating smooth transition via tempo adjustment and sound effect insertion, the listening experience can be largely enhanced.

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.

A convenient video browsing system for popular sports such as baseball, tennis and billiards is proposed in this work. A sports video is automatically segmented into video clips and annotated with semantic concepts in terms of event type. For sports with specific game structure, e.g. baseball and tennis, we further analyze the entire video of the match with the aid of caption information, webcast information, and the domain knowledge of the corresponding sport. Each segmented video clip with semantic annotation is then mapped to a certain part of the game structure. Finally, the proposed system, name as Sports Wizard, provides a favorable way for the user to browse sports videos based on semantic concepts or game structure.

Wedding is one of the most important ceremonies in our lives. It symbolizes the birth and creation of a new family. In this paper, we present a system for automatically segmenting a wedding ceremony video into a sequence of recognizable wedding events, e.g., the couple's wedding kiss. Our goal is to develop an automatic tool that helps users to efficiently organize, search, and retrieve his/her treasured wedding memories. Furthermore, the obtained event descriptions could benefit and complement the current research in semantic video understanding. Based on the knowledge of wedding customs, a set of audiovisual features, relating to the wedding contexts of speech/music types, applause activities, picture-taking activities, and leading roles, are exploited to build statistical models for each wedding event. Thirteen wedding events are then recognized by a hidden Markov model, which takes into account both the fitness of observed features and the temporal rationality of event ordering to improve the segmentation accuracy. We conducted experiments on a collection of wedding videos and the promising results demonstrate the effectiveness of our approach. Comparisons with conditional random fields show that the proposed approach is more effective in this application domain.