PoseTrack: A Benchmark for Human Pose Estimation and Tracking

Human poses and motions are important cues for analysis of videos with people and there is strong evidence that representations based on body pose are highly effective for a variety of tasks such as activity recognition, content retrieval and social signal processing. In this work, we aim to further advance the state of the art by establishing "PoseTrack", a new large-scale benchmark for video-based human pose estimation and articulated tracking, and bringing together the community of researchers working on visual human analysis. The benchmark encompasses three competition tracks focusing on i) single-frame multi-person pose estimation, ii) multi-person pose estimation in videos, and iii) multi-person articulated tracking. To facilitate the benchmark and challenge we collect, annotate and release a new %large-scale benchmark dataset that features videos with multiple people labeled with person tracks and articulated pose. A centralized evaluation server is provided to allow participants to evaluate on a held-out test set. We envision that the proposed benchmark will stimulate productive research both by providing a large and representative training dataset as well as providing a platform to objectively evaluate and compare the proposed methods. The benchmark is freely accessible at https://posetrack.net.Comment: www.posetrack.ne

Energy Minimization for Multiple Object Tracking

Multiple target tracking aims at reconstructing trajectories of several moving targets in a dynamic scene, and is of significant relevance for a large number of applications. For example, predicting a pedestrian’s action may be employed to warn an inattentive driver and reduce road accidents; understanding a dynamic environment will facilitate autonomous robot navigation; and analyzing crowded scenes can prevent fatalities in mass panics. The task of multiple target tracking is challenging for various reasons: First of all, visual data is often ambiguous. For example, the objects to be tracked can remain undetected due to low contrast and occlusion. At the same time, background clutter can cause spurious measurements that distract the tracking algorithm. A second challenge arises when multiple measurements appear close to one another. Resolving correspondence ambiguities leads to a combinatorial problem that quickly becomes more complex with every time step. Moreover, a realistic model of multi-target tracking should take physical constraints into account. This is not only important at the level of individual targets but also regarding interactions between them, which adds to the complexity of the problem. In this work the challenges described above are addressed by means of energy minimization. Given a set of object detections, an energy function describing the problem at hand is minimized with the goal of finding a plausible solution for a batch of consecutive frames. Such offline tracking-by-detection approaches have substantially advanced the performance of multi-target tracking. Building on these ideas, this dissertation introduces three novel techniques for multi-target tracking that extend the state of the art as follows: The first approach formulates the energy in discrete space, building on the work of Berclaz et al. (2009). All possible target locations are reduced to a regular lattice and tracking is posed as an integer linear program (ILP), enabling (near) global optimality. Unlike prior work, however, the proposed formulation includes a dynamic model and additional constraints that enable performing non-maxima suppression (NMS) at the level of trajectories. These contributions improve the performance both qualitatively and quantitatively with respect to annotated ground truth. The second technical contribution is a continuous energy function for multiple target tracking that overcomes the limitations imposed by spatial discretization. The continuous formulation is able to capture important aspects of the problem, such as target localization or motion estimation, more accurately. More precisely, the data term as well as all phenomena including mutual exclusion and occlusion, appearance, dynamics and target persistence are modeled by continuous differentiable functions. The resulting non-convex optimization problem is minimized locally by standard conjugate gradient descent in combination with custom discontinuous jumps. The more accurate representation of the problem leads to a powerful and robust multi-target tracking approach, which shows encouraging results on particularly challenging video sequences. Both previous methods concentrate on reconstructing trajectories, while disregarding the target-to-measurement assignment problem. To unify both data association and trajectory estimation into a single optimization framework, a discrete-continuous energy is presented in Part III of this dissertation. Leveraging recent advances in discrete optimization (Delong et al., 2012), it is possible to formulate multi-target tracking as a model-fitting approach, where discrete assignments and continuous trajectory representations are combined into a single objective function. To enable efficient optimization, the energy is minimized locally by alternating between the discrete and the continuous set of variables. The final contribution of this dissertation is an extensive discussion on performance evaluation and comparison of tracking algorithms, which points out important practical issues that ought not be ignored

Comparison of the scientific performance in hip and knee arthroplasty between the leading continents

Background: Scientific progress in the field of knee and hip arthroplasty has enabled the preservation of mobility and quality of life in the case of patients with many primary degenerative and (post-) traumatic joint diseases. This comparative study aims to investigate differences in scientific performance between the leading continents in the field of hip and knee arthroplasty. Methods: Using specific search terms all studies published by the scientific leading continents Europe, North America, Asia and Oceania listed in the Web of Science databases were included. All identified publications were analysed and comparative conclusions were drawn regarding the qualitative and quantitative scientific merit of each continent. Results: Europe, followed by North America, Asia, and Oceania, had the highest overall number of publications in the field of arthroplasty. Since 2000, there has been a strong increase in knee arthroplasty publication rate, particular pronounced in Asia. Studies performed and published in North America and those on knee arthroplasty received the highest number of fundings. Publications regarding hip arthroplasty achieved the highest average citation rate. In contradistinction to the others, in North America most funding was provided by private agencies. Conclusion: Although Europe showed the highest total number of publications, authors and institutions, arthroplasty research from North America received greater scientific attention and financial support. Measured by citations, publications on hip arthroplasty attained higher scientific interest and studies on knee arthroplasty received higher economic affection

Subgroup analysis of scientific performance in the field of arthroplasty

Introduction: Arthroplasty is the final treatment option for maintaining mobility and quality of life in many primary degenerative and (post-) traumatic joint diseases. Identification of research output and potential deficits for specific subspecialties may be an important measure to achieve long-term improvement of patient care in this field. Methods: Using specific search terms and Boolean operators, all studies published since 1945 to the subgroups of arthroplasty listed in the Web of Science Core Collection were included. All identified publications were analysed according to bibliometric standards, and comparative conclusions were drawn regarding the scientific merit of each subgroup. Results: Most publications investigated the subgroups of septic surgery and materials followed by approach, navigation, aseptic loosening, robotic and enhanced recovery after surgery (ERAS). In the last 5 years, research in the fields of robotic and ERAS achieved the highest relative increase in publications In contrast, research on aseptic loosening has continued to lose interest over the last 5 years. Publications on robotics and materials received the most funding on average while those on aseptic loosening received the least. Most publications originated from USA, Germany, and England, except for research on ERAS in which Denmark stood out. Relatively, publications on aseptic loosening received the most citations, whereas the absolute scientific interest was highest for the topic infection. Discussion: In this bibliometric subgroup analysis, the primary scientific outputs focused on septic complications and materials research in the field of arthroplasty. With decreasing publication output and the least financial support, intensification of research on aseptic loosening is urgently recommended

Voice Operated Information System in Slovak

Speech communication interfaces (SCI) are nowadays widely used in several domains. Automated spoken language human-computer interaction can replace human-human interaction if needed. Automatic speech recognition (ASR), a key technology of SCI, has been extensively studied during the past few decades. Most of present systems are based on statistical modeling, both at the acoustic and linguistic levels. Increased attention has been paid to speech recognition in adverse conditions recently, since noise-resistance has become one of the major bottlenecks for practical use of speech recognizers. Although many techniques have been developed, many challenges still have to be overcome before the ultimate goal -- creating machines capable of communicating with humans naturally -- can be achieved. In this paper we describe the research and development of the first Slovak spoken language dialogue system. The dialogue system is based on the DARPA Communicator architecture. The proposed system consists of the Galaxy hub and telephony, automatic speech recognition, text-to-speech, backend, transport and VoiceXML dialogue management modules. The SCI enables multi-user interaction in the Slovak language. Functionality of the SLDS is demonstrated and tested via two pilot applications, ``Weather forecast for Slovakia'' and ``Timetable of Slovak Railways''. The required information is retrieved from Internet resources in multi-user mode through PSTN, ISDN, GSM and/or VoIP network