Click Carving: Segmenting Objects in Video with Point Clicks

We present a novel form of interactive video object segmentation where a few clicks by the user helps the system produce a full spatio-temporal segmentation of the object of interest. Whereas conventional interactive pipelines take the user's initialization as a starting point, we show the value in the system taking the lead even in initialization. In particular, for a given video frame, the system precomputes a ranked list of thousands of possible segmentation hypotheses (also referred to as object region proposals) using image and motion cues. Then, the user looks at the top ranked proposals, and clicks on the object boundary to carve away erroneous ones. This process iterates (typically 2-3 times), and each time the system revises the top ranked proposal set, until the user is satisfied with a resulting segmentation mask. Finally, the mask is propagated across the video to produce a spatio-temporal object tube. On three challenging datasets, we provide extensive comparisons with both existing work and simpler alternative methods. In all, the proposed Click Carving approach strikes an excellent balance of accuracy and human effort. It outperforms all similarly fast methods, and is competitive or better than those requiring 2 to 12 times the effort.Comment: A preliminary version of the material in this document was filed as University of Texas technical report no. UT AI16-0

Efficient MRF Energy Propagation for Video Segmentation via Bilateral Filters

Segmentation of an object from a video is a challenging task in multimedia applications. Depending on the application, automatic or interactive methods are desired; however, regardless of the application type, efficient computation of video object segmentation is crucial for time-critical applications; specifically, mobile and interactive applications require near real-time efficiencies. In this paper, we address the problem of video segmentation from the perspective of efficiency. We initially redefine the problem of video object segmentation as the propagation of MRF energies along the temporal domain. For this purpose, a novel and efficient method is proposed to propagate MRF energies throughout the frames via bilateral filters without using any global texture, color or shape model. Recently presented bi-exponential filter is utilized for efficiency, whereas a novel technique is also developed to dynamically solve graph-cuts for varying, non-lattice graphs in general linear filtering scenario. These improvements are experimented for both automatic and interactive video segmentation scenarios. Moreover, in addition to the efficiency, segmentation quality is also tested both quantitatively and qualitatively. Indeed, for some challenging examples, significant time efficiency is observed without loss of segmentation quality.Comment: Multimedia, IEEE Transactions on (Volume:16, Issue: 5, Aug. 2014

A video object generation tool allowing friendly user interaction

In this paper we describe an interactive video object segmentation tool developed in the framework of the ACTS-AC098 MOMUSYS project. The Video Object Generator with User Environment (VOGUE) combines three different sets of automatic and semi-automatic-tool (spatial segmentation, object tracking and temporal segmentation) with general purpose tools for user interaction. The result is an integrated environment allowing the user-assisted segmentation of any sort of video sequences in a friendly and efficient manner.Peer ReviewedPostprint (published version

Image sequence analysis for emerging interactive multimedia services - The European COST 211 framework

Cataloged from PDF version of article.Flexibility and efficiency of coding, content extraction, and content-based search are key research topics in the field of interactive multimedia. Ongoing ISO MPEG-4 and MPEG-7 activities are targeting standardization to facilitate such services. European COST Telecommunications activities provide a framework for research collaboration. COST 211bis and COST 211ter activities have been instrumental in the definition and development of the ITU-T H.261 and H.263 standards for videoconferencing over ISDN and videophony over regular phone lines, respectively. The group has also contributed significantly to the ISO MPEG-4 activities. At present a significant effort of the COST 211ter group activities is dedicated toward image and video sequence analysis and segmentation—an important technological aspect for the success of emerging object-based MPEG-4 and MPEG-7 multimedia applications. The current work of COST 211 is centered around the test model, called the Analysis Model (AM). The essential feature of the AM is its ability to fuse information from different sources to achieve a high-quality object segmentation. The current information sources are the intermediate results from frame-based (still) color segmentation, motion vector based segmentation, and changedetection-based segmentation. Motion vectors, which form the basis for the motion vector based intermediate segmentation, are estimated from consecutive frames. A recursive shortest spanning tree (RSST) algorithm is used to obtain intermediate color and motion vector based segmentation results. A rule-based region processor fuses the intermediate results; a postprocessor further refines the final segmentation output. The results of the current AM are satisfactory; it is expected that there will be further improvements of the AM within the COST 211 project