Topology dictionary with Markov model for 3D video content-based skimming and description

This paper presents a novel approach to skim and de-scribe 3D videos. 3D video is an imaging technology which consists in a stream of 3D models in motion captured by a synchronized set of video cameras. Each frame is composed of one or several 3D models, and therefore the acquisition of long sequences at video rate requires massive storage de-vices. In order to reduce the storage cost while keeping rele-vant information, we propose to encode 3D video sequences using a topology-based shape descriptor dictionary. This dictionary is either generated from a set of extracted pat-terns or learned from training input sequences with seman-tic annotations. It relies on an unsupervised 3D shape-based clustering of the dataset by Reeb graphs, and features a Markov network to characterize topological changes. The approach allows content-based compression and skimming with accurate recovery of sequences and can handle com-plex topological changes. Redundancies are detected and skipped based on a probabilistic discrimination process. Semantic description of video sequences is then automat-ically performed. In addition, forthcoming frame encoding is achieved using a multiresolution matching scheme and allows action recognition in 3D. Our experiments were per-formed on complex 3D video sequences. We demonstrate the robustness and accuracy of the 3D video skimming with dramatic low bitrate coding and high compression ratio. 1

Detecting human heads with their orientations

We propose a two-step method for detecting human heads with their orientations. In the first step, the method employs an ellipse as the contour model of human-head appearances to deal with wide variety of appearances. Our method then evaluates the ellipse to detect possible human heads. In the second step, on the other hand, our method focuses on features inside the ellipse, such as eyes, the mouth or cheeks, to model facial components. The method evaluates not only such components themselves but also their geometric configuration to eliminate false positives in the first step and, at the same time, to estimate face orientations. Our intensive experiments show that our method can correctly and stably detect human heads with their orientations

Shape from shading with interreflections under proximal light source - 3D shape reconstruction of unfolded book surface from a scanner image

We address the problem to recover the 3D shape of an unfolded book surface from the shading information in a scanner image. From a technical point of view, this shape from shading problem in real world environments is characterized by (1) proximal light source, (2) interreflections, (3) moving light source, (4) specular reflection, and (5) nonuniform albedo distribution. Taking all these factors into account, we first formulate the problem based on an iterative nonlinear optimization scheme. Then we introduce piecewise polynomial models of the 3D shape. Image restoration experiments for a real book surface demonstrated that geometric and photometric distortions are almost completely removed by the proposed method</p

Energy on demand: Efficient and versatile energy control system for home energy management

Abstract—We have been proposing the concept of “i-Energy ” as a new energy management scheme to realize efficient and versatile control of e-power flows among decentralized energy generation/storage devices and appliances in homes, offices, and neighboring communities. The i-Energy concept is best characterized by a novel energy control method named “Energy on Demand (EoD). ” The novelties of EoD rest in (1) the explicit demand-based power supply control, (2) the best-effort power distribution based on appliance priorities, and (3) the ceiling control of power consumption. With EoD, people can attain the guaranteed reduction of energy consumption without damaging their quality of lives. Moreover, when utility companies are allowed to set and modify ceiling values based on contracts with consumers, EoD systems work as smart demand response systems. This paper first describes the protocol for EoD: power request demands named &quot;Quality of Energy (QoEn) &quot; and appliance priority descriptions. Then, the demand mediation algorithm based on appliance priorities for a single power source is introduced. Experiments using real world everyday-life data in a smart apartment room demonstrated the effectiveness of EoD

Finding Kinematic Structure in Time Series Volume Data

This paper presents a new scheme for acquiring 3D kinematic structure and motion from time series volume data. Our basic strategy is to first represent the shape structure of the target in each frame by Reeb graph which we compute by using geodesic distance of target's surface, and then estimate the kinematic structure of the target which is consistent with these shape structures. Although the shape structures can be very different from frame to frame, we propose to derive a unique kinematic structure by way of clustering some nodes of graph, based on the fact that they are partly coherent to a certain extent of time series. Once we acquire a unique kinematic structure, we fit it to other Reeb graphs in the remaining frames, and describe the motion throughout the entire time series. The only assumption we make is that human body can be approximated by an articulated body with certain numbers of end-points and branches. We demonstrate the efficacy of the proposed scheme through some experiments