Frame-based Approach Research Articles

A template-based baseball video scene classification using efficient playfield segmentation

In this paper, we present an effective and efficient framework for baseball video scene classification. The results of scene classification can be able to provide the ground for baseball video abstraction and high-level event extraction. In general, most conventional approaches are shot-based, which shot change detection and key-frame extraction are necessary prerequisite procedures. On the contrary, we propose a frame-based approach. In our scene classification framework, an efficient playfield segmentation technique is proposed, and then the reduced field maps are utilized as scene templates. Because the shot change detection and the key-frame extraction are not required in proposed method, the new framework is very simple and efficient. The experimental results have demonstrated that the effectiveness of our proposed framework for baseball videos scene classification, and it can be easily extended the template-based approach to other kinds of sports videos.

Frame-based guide to situated decision-making on climate change

The present paper describes a frame-based approach to situated-decision-making on climate change. Building on the multidisciplinary literature on the relationship between frames and decision-making, it argues that decision-makers may gain from making frames more explicit and using them for generating different visions about the central issues. Frames act as organizing principles that shape in a “hidden” and taken-for-granted way how people conceptualize an issue. Science-related issues, such as climate change, are often linked to only a few frames, which consistently appear across different policy areas. Indeed, it appears that there are some very contrasting ways in which climate change may be framed. These frames can be characterized in terms of a simple framework that highlights specific interpretations of climate issues. A second framework clarifies the built-in frames of decision tools. Using Thompson's two basic dimensions of decision, it identifies the main uncertainties that should be considered in developing a decision strategy. The paper characterizes four types of decision strategy, focusing on (1) computation, (2) compromise, (3) judgment, or (4) inspiration, and links each strategy to the appropriate methods and tools, as well as the appropriate social structures. Our experiences show that the frame-based guide can work as an eye-opener for decision-makers, particularly where it demonstrates how to add more perspectives to the decision.

Optimal scheduling for dynamic channel allocation in wireless LANs

Channel allocation schemes that have been used in cellular wireless networks have limited applicability to wireless LANs (WLANs) because of the small number of available channels and irregular cell geometries in WLAN environments. In this paper, we propose a dynamic, frame-based channel allocation architecture for WLANs. In this architecture, time is divided into a sequence of consecutive frames (in the order of milliseconds), and in each frame, only a non-interfering subset of access points (APs) is activated. Under broad traffic assumptions, we prove that the attainable system throughput can be optimized by scheduling APs and allocating channels in each frame such that a weighted sum of queue sizes at the activated APs is maximized. This optimality criterion for AP scheduling and channel allocation leads to a novel graph problem which is a variant of the well-known maximum independent set problem. We develop an approximation algorithm that has quadratic time complexity (in the number of APs) and, under certain conditions, yields a constant (6) factor approximation bound. Using the ns2 simulator we conducted experiments to compare our frame-based approach to static channel allocation. Results of our simulation indicate that our approach is able to deliver system throughput improvements of more than 50%.

A frame-based approach for wideband correlation-inversion of lossless scatterers

Presented here is an ultra-wideband-correlation-based scheme for imaging and inversion of an unknown weak and lossless scatterer embedded in a known background medium. The scheme uses an excitation and reception of ultra wideband/short-pulsed fields by an array of transducers located outside the imaging domain. The scatterer image is formed by cross correlating (in the short-pulsed domain or via spectral integration in the ultra wideband domain) the numerically/analytically back-propagated, measured, and scattered data set with the forward-propagation excitations. It is shown that in the ultra wideband domain, the forward-backward propagation functions form a frame set in a finite Hilbert space. Within the weak scattering assumption (Born approximation) the scatterer's image and object function (velocity profile) are related via the corresponding frame operator. Therefore, an exact inversion scheme of the frame operator is readily available to yield the object function via an iterative scheme or using the dual frame set. Numerical examples that demonstrate the performance of the imaging and inversion schemes for scatterers with various velocity profiles are presented. It is shown that the scatterer image is generally of poor resolution. However, on inversion, a high-quality velocity profile is obtained that captures the scatterer fine details.

Frame-Based Stereotactic Resection of Subcentimeter Arteriovenous Malformations in Deep or Eloquent Regions of the Brain: Indications and Technique with Eight Consecutive Operations

Subcentimeter arteriovenous malformations (AVMs) located in deep or eloquent cortex can be difficult to localize intraoperatively and safely remove with surgery. Nevertheless, surgical resection may be the optimal definitive treatment option available for select patients. In this communication, we describe our experience using a framed-based stereotactic approach for resecting these AVMs. The operative records of all AVMs treated at our institution over an 8-year period (1996-2004) were reviewed. 180 surgically treated AVMs were identified. From this group of patients, frame-based stereotaxy was used for 8 AVMs (4.4%) in 7 patients. The angiograms, operative reports, and medical records for these 7 patients were retrospectively reviewed with attention to neurological outcome, extent of AVM obliteration, and anatomic factors that impacted the decision to employ a frame-based stereotactic approach. All AVMs removed with this technique were less than 1 cm in diameter. Angiography confirmed complete resection in all cases. No new neurological deficits occurred in any patient. By providing highly accurate three-dimensional nidus localization and minimizing approach-related brain manipulation, frame-based stereotaxy reduces the morbidity associated with resection of subcentimeter AVMs located in deep or eloquent regions of the brain. This technique makes a definitive surgical cure available to patients who otherwise would only be considered for radiosurgery.

On Pose Estimation for Human-Robot Symbiosis

This paper presents a vision based pose estimation system using knowledge based approach for human-robot symbiosis. The system is based on visual information of the face by connected component analysis of the skin color segmentation of images in HSV color model and is commenced with the face recognition and pose classification scheme using subspace PCA based pattern-matching strategies. With the knowledge of the known user's profile, face poses are then classified by multilayer perceptron. Based on the frame-based knowledge representation approach, face poses are being interpreted using the Software Platform for Agent and Knowledge (SPAK) management. On face pose recognition, robot is then instructed to perform some specific tasks by issuing pose commands. Experimental results demonstrate that the subspace method is better than that of the standard PCA method for face pose classification. The system has been demonstrated with the implementation of the algorithm to interact with an entertainment robot named, AIBO for human-robot symbiotic relationship.

Frame-based approach for peak-to-average power ratio reduction in OFDM

A new method for reducing the peak-to-average power ratio (PAPR) in orthogonal frequency-division multiplexing is proposed. The new method, called erasure pattern selection (EPS), is based on the use of frame expansion for adding redundancy to the data. Part of the redundancy is removed by examining several patterns for erasing subcarriers and selecting the pattern that produces the lowest PAPR for transmission. The residual redundancy in the data is exploited at the receiver to aid both the reconstruction of the erased data and correction of errors. The implementation is aided with the incorporation of a projection-onto-convex-sets (POCS) method in EPS in order to select and assign the best values to the unused subcarriers and further reduce the PAPR. Complexity analysis and simulation results show that the POCS-based EPS method outperforms existing probabilistic methods, while requiring lower overall complexity

Frameless Stereotactic Radiosurgery of a Solitary Liver Metastasis Using Active Breathing Control and Stereotactic Ultrasound

Radiosurgery of liver metastases is effective but a technical challenge due to respiration-induced movement. The authors report on the initial experience of the combination of active breathing control (ABC) with stereotactic ultrasound (B-mode acquisition and targeting [BAT]) for frameless radiosurgery. A patient with a solitary, inoperable liver metastasis from cholangiocellular carcinoma is presented (Figure 4). ABC (Figure 3) was used for tumor/liver immobilization. Tumor/liver position was controlled and corrected using ultrasound (BAT; Figure 1). The tumor was irradiated with a single dose of 24 Gy. Using ABC, the motion of the tumor was significantly reduced and the overall positioning error was < 5 mm (Figure 2). BAT allowed a rapid localization of the lesion during breath hold which could be performed without difficulties for 20 s. Overall treatment time was acceptable (30 min). Frameless stereotactic radiotherapy with the combination of ABC and BAT allows the delivery of high single doses to targets accessible to ultrasound with high precision comparable to a frame-based approach.

A frame-based approach to case alternations: The swarm-class verbs in Czech

Abstract This paper explores the complex relationship between the meaning of predicates and the morphosyntactic expression of their arguments, as manifested in the swarm-class alternations in Czech. One way of getting at the nature of the alternations is to take a frame-semantic approach, which allows us to introduce the notion of scene as an important factor in linking relationships. It is proposed that linking patterns are organized in a network of generalized scene types, each of which represents a particular role configuration structured in such a way that one of its roles can be singled out as the vantage point from which that event type is conventionally presented in a particular diathesis; the analysis argues for the notion of viewpoint as an event-structuring concept (distinct from discourse-based topicness) that is directly reflected in certain conventionalized linking patterns. The results of the investigation show that what may appear to be hard-to-predict variations in subject selection can be treated as instances of regular linking relations.

Frame-based stereotactic biopsy remains an important diagnostic tool with distinct advantages over frameless stereotactic biopsy

As the availability of image-guided surgical navigation systems has increased, the application of frame-based biopsy has declined at our institution, despite equivalent accuracy and safety. There are several cost issues separating the use of surgical navigation systems and stereotactic frames for simple biopsy which may have implications in this era of health care cost control. We retrospectively reviewed the UCSF experience with stereotactic brain biopsy from a 9 year period. Data were collected for 213 consecutive stereotactic brain biopsies performed at UCSF (139 frame-based and 74 frameless). There were no significant differences between the frame-based and frameless biopsy groups with regard to patient demographics, overall histopathology, proportion of nondiagnostic biopsies, or incidence of complications. General anesthesia was used for 9 (6%) and 70 (95%) of the frame-based and frameless biopsy cases, respectively. Frame-based biopsies required a mean of 114+/-3 min of operating room time, while frameless biopsies required 185+/-6 min (P<0.0001). For patients admitted to our neurosurgery service who underwent frame-based (n=110) or frameless (n=52) biopsy within 24 h of admission, the mean lengths of hospital stay were 1.8+/-0.2 and 3.2+/-0.6 days, respectively (P=0.007). Frame-based and frameless stereotactic biopsy approaches were equally effective at providing a tissue diagnosis with minimum morbidity and mortality. The frame-based approach, however, required significantly less anesthesia resources, less operating room time and shorter hospital stays, and thus should still be considered a first-line approach for stereotactic brain biopsy.

Object watermarks for digital images and video

The growth of new image technologies has created a need for techniques that can be used for copyright protection of digital images and video. One approach for copyright protection is to introduce an invisible signal, known as a digital watermark, into an image or video sequence. With the development of MPEG-4, frame-based approach has been migrating to object-based approach. Therefore, object-based watermarking schemes are needed. In this article, we propose a novel blind object watermarking scheme for images and video using shape adaptive-discrete wavelet transform (SA-DWT). To make the watermark robust and perceptual invisible, we embed it in the weighting mean of the wavelet blocks using the quantisation visual model based on the human visual system. Watermark detection is accomplished without the original, unwatermarked object by using statistical detection technique. Experimental results demonstrate that the proposed watermarking scheme is perceptual invisible and robust against many attacks such as lossy image/video compression (e.g. JPEG, JPEG2000 and MPEG-4), scaling, adding noise, filtering, D/A and A/D conversion, etc.

Motion estimation using a frame-based adaptive thresholding approach

This paper proposes two frame-based adaptive thresholding algorithms for reducing the amount of computation involved in block-based motion estimation in the real-time and low-rate video coders. The proposed algorithms use an adaptive threshold for each of the frames to prejudge if each of the block matching computation is worthwhile. Based on the difference between the current and reference frames, the first algorithm determines a threshold in terms of the optimal trade-off between run-time and distortion, and the second algorithm determines a threshold according to a user specified percentage of total number of blocks. The experimental results demonstrate that the proposed algorithms can significantly reduce the amount of computation compared to the previous algorithms, while almost fully maintaining the quality of the reconstructed image.

The Application Accuracy of the NeuroMate Robot—A Quantitative Comparison with Frameless and Frame-Based Surgical Localization Systems

The NeuroMate™ robot system (Integrated Surgical Systems, Davis, CA) is a commercially available, image-guided, robotic-assisted system used for stereotactic procedures in neurosurgery. In this article, we present a quantitative comparison of the application accuracy of the NeuroMate with that of standard frame-based and frameless stereotactic techniques. The article discusses a five-way application accuracy comparison study. The variables of our comparison and their mean errors are as follows: (1) with the robot in a frame-based configuration, the RMS was 0.86 ± 0.32 mm; (2) with the robot in the frameless configuration, the RMS was 1.95 ± 0.44 mm; (3) in a standard stereotactic (ZD) frame-based approach, the RMS was 1.17 ± 0.25 mm; (4) with an infrared tracking system using the frame for fiducial registration, the RMS was 1.47 ± 0.45 mm; (5) with an infrared tracking system using screw markers for registration, the RMS was 0.68 ± 0.26 mm. The study was performed with 2-mm sections of CT scans. These results show that the application accuracy of the frame-based NeuroMate robot is comparable to that of standard localizing systems, whedier they are frame-based or infrared tracked.

An object-oriented frame-based prototyping approach for the development of automated manufacturing systems

Prototyping assumes a predominant role in the development of automated manufacturing systems (AMSs) and, in particular, in the verification of system specifications prior to their subsequent realization. In recent years, object-oriented methods have been applied increasingly in the prototyping of AMSs to shorten the development cycle. This paper proposes an object-oriented frame-based approach to the rapid prototyping of AMSs. The proposed approach is characterized by the extended use of the frame-based representation method in the modelling of object behaviour. This approach also draws reference from an object-oriented conceptual model of manufacturing systems and a semantic model of object behaviour. These two models and an object-oriented frame-based prototyping tool are developed to support the approach. When compared with the conventional object-oriented methods, the proposed approach can reduce the semantic gap in system modelling and therefore lead to a better integration of the specification and prototyping of AMSs. The application of the proposed approach is illustrated by the prototyping of a flexible manufacturing system.

Asset-based system and software system development — A frame-based approach

Previous works on software reusability has shown that an asset-based systems development strategy to software reuse is effective in identifying reusable design components. This strategy requires moving away from traditional and stand-alone applications development toward an integrated approach. This paper will review previous work on using frames for knowledge representation and will show how an implementation strategy based on the frame-based representation can be useful as a possible implementation approach for the asset-based systems development strategy.

Segmental probability distribution model approach for isolated Mandarin syllable recognition

A segmental probability distribution model (SPDM) approach is proposed for fast and accurate recognition of isolated Mandarin syllables. Instead of the conventional frame-based approach such as the hidden Markov model (HMM), the model matching process in the proposed SPDM is evaluated segment-by-segment based on information-theoretic distance measurements. The training and recognition procedures for the SPDM are developed first. Several distance measurement criteria, including the Chernoff distance, Bhattacharyya distance, Patrick–Fisher distance, divergence and a Bayesian-like distance, are used, and formulations and comparative results are discussed. Experimental results show that, compared to the widely used sub-unit based continuous density HMM, the proposed method leads to an improvement of 15.27% in the error rate, with a 12-fold increase in recognition speed and less than three quarters of the mixture requirements.

Frame-based safety analysis approach for decision-based errors

A frame-based approach is proposed to analyze decision-based errors made by automatic controllers or human operators due to erroneous reference frames. An integrated framework, Two Frame Model (TFM), is first proposed to model the dynamic interaction between the physical process and the decision-making process. Two important issues, consistency and competing processes, are raised. Consistency between the physical and logic frames makes a TFM-based system work properly. Loss of consistency refers to the failure mode that the logic frame does not accurately reflect the state of the controlled processes. Once such failure occurs, hazards may arise. Among potential hazards, the competing effect between the controller and the controlled process is the most severe one, which may jeopardize a defense-in-depth design. When the logic and physical frames are inconsistent, conventional safety analysis techniques are inadequate. We propose Frame-based Fault Tree; Analysis (FFTA) and Frame-based Event Tree Analysis (FETA) under TFM to deduce the context for decision errors and to separately generate the evolution of the logical frame as opposed to that of the physical frame. This multi-dimensional analysis approach, different from the conventional correctness-centred approach, provides a panoramic view in scenario generation. Case studies using the proposed techniques are also given to demonstrate their usage and feasibility.

Knowledge-based algorithm construction for real-world engineering PDEs

Work to develop a robust knowledge-base for the automated construction of numerical algorithms is described. The approach adopted is one of synthesis of an algorithm from a library of pre-formed sub-components. The target domain for the system is Finite Element Analysis of incompressible fluid dynamics and heat transfer. The knowledge being used is described and illustrated with numerous examples. A conceptual knowledge representation and inferencing control mechanism employing the blackboard paradigm with autonomous knowledge agents and implemented via a frame-based approach is proposed.

Knowledge-based feature recognizer for machining

Various methods of input format to manufacturing systems have been proposed. For an integrated manufacturing system, direct CAD data input is the most appropriate input format. Currently, the identification of general machinable features is limited in scope. The application of many feature recognition systems has not yet been tested thoroughly enough to verify their suitability for manufacturing activities, therefore a suitable feature recognizer is required. A software tool, GoldWorks III TM has been used to develop a knowledge-based feature modeller for machining. A frame-based approach to formulate a lattice structure of machining features is used to represent rotationally symmetric components.

A frame-based approach to conformance testing

This paper presents the usage of the frame-based knowledge representation method for protocol specification, and shows its application in conformance testing and test sequence generation.