8803958
Participatory design with individuals who have amnesia
We present experiences and insights into participatory design with individuals who have anterograde amnesia and therefore have extreme difficulty storing new memories. We discuss our design of the design process, and present a set of techniques used to support memory during and between design sessions. From this experience, we identify cognitive assumptions of participatory design that break down when working with amnestics. We generalize these ideas into an analytical framework for researchers and practitioners who intend to use participatory design with persons having various kinds of cognitive impairments. We illustrate the framework by analyzing a cognitive deficit unrelated to memory that we encountered, and an unanticipated benefit from what at first appeared to be a liability in working with this design team.
207583051
Multi-finger and whole hand gestural interaction techniques for multi-user tabletop displays
Recent advances in sensing technology have enabled a new generation of tabletop displays that can sense multiple points of input from several users simultaneously. However, apart from a few demonstration techniques [17], current user interfaces do not take advantage of this increased input bandwidth. We present a variety of multifinger and whole hand gestural interaction techniques for these displays that leverage and extend the types of actions that people perform when interacting on real physical tabletops. Apart from gestural input techniques, we also explore interaction and visualization techniques for supporting shared spaces, awareness, and privacy. These techniques are demonstrated within a prototype room furniture layout application, called RoomPlanner.
9371851
Under My Finger: Human Factors in Pushing and Rotating Documents Across the Table
When passing a document to someone across a table, the person passing the document often rotates it to face the receiver. In this paper, we present the results of a user evaluation of three Push-and-Rotate schemes that offer different underlying control semantics for how an electronic document can automatically rotate as it is pushed across an interactive tabletop surface. The effects of document size are also discussed.
367658
Informing the Design of Direct-Touch Tabletops
Tables provide a large and natural interface for supporting direct manipulation of visual content for human-to-human interactions. Such surfaces also support collaboration, coordination, and parallel problem solving. However, the direct-touch table metaphor also presents considerable challenges, including the need for input methods that transcend traditional mouse- and keyboard-based designs. In this paper, we've designed, implemented, and studied a variety of tabletop user interfaces, interaction techniques, and usage scenarios
8182719
Participatory design of an orientation aid for amnesics
We present the participatory design and evaluation of an orientation aid for individuals who have anterograde amnesia. Our design team included six amnesics who have extreme difficulty storing new memories. We describe the methods we used to enable the participation of individuals with such severe cognitive impairments. Through this process, we have conceived, designed, and developed the OrientingTool, a software application for Personal Digital Assistants that can be used by amnesics to orient themselves when feeling lost or disoriented. Two complementary studies were conducted to evaluate the effectiveness of this tool in ecologically valid contexts. Our findings suggest that the OrientingTool can improve an amnesic's independence and confidence in managing situations when disoriented, and that participatory design may be productively used with participants who have significant cognitive disabilities.
11926246
Data Hiding in Compiled Program Binaries for Enhancing Computer System Performance
Information hiding has been studied in many security applications such as authentication, copyright management and digital forensics. In this work, we introduce a new application where successful information hiding in compiled program binaries could bring system-wide performance improvements. Our goal is to enhance computer system performance by providing additional information to the processor, without changing the instruction set architecture. We first analyze the statistics of typical programs to demonstrate the feasibility of hiding data in them. We then propose several techniques to hide a large amount of data in the operand fields with very low computation and storage requirements during the extraction process. The data embedding is made reversible to recover the original instructions and to ensure the correct execution of the computer program. Our experiments on the SPEC CPU2000 benchmark programs show that up to 110K bits of information can be embedded in large programs with as little as 3K bits of additional run-time memory in the form of a simple look-up table.
16312232
An algorithm for wipe detection
The detection of transitions between shots in video programs is an important first step in analyzing video content. The wipe is a frequently used transitional form between shots. Wipe detection is more involved than the detection of abrupt and other gradual transitions because a wipe may take various patterns and because of the difficulty in discriminating a wipe from object and camera motion. In this paper, we propose an algorithm for detecting wipes using both structural and statistical information. The algorithm can effectively detect most wipes used in current TV programs. It uses the DC sequence which can be easily extracted from the MPEG stream without full decompression.
3261989
Robust error-resilient approach for MPEG video transmission over Internet
In network delivery of compressed video, packets may be lost if the channel is unreliable. Such losses tend to occur in burst. In this paper, we develop an error resilient video encoding approach to help error concealment at the decoder. We introduce a new block shuffling scheme to isolate erroneous blocks caused by packet losses. And we apply data hiding to add additional protection for motion vectors. The incorporation of these scheme adds little complexity to the standard encoder. Experimental results suggest that our approach can achieve a reasonable quality for packet loss up to 30% over a wide range of video materials.
18579408
Image Tampering Identification using Blind Deconvolution
Digital images have been used in growing number of applications from law enforcement and surveillance, to medical diagnosis and consumer photography. With such widespread popularity and the presence of low-cost image editing softwares, the integrity of image content can no longer be taken for granted. In this paper, we propose a novel technique based on blind deconvolution to verify image authenticity. We consider the direct output images of a camera as authentic, and introduce algorithms to detect further processing such as tampering applied to the image. Our proposed method is based on the observation that many tampering operations can be approximated as a combination of linear and non-linear components. We model the linear part of the tampering process as a filter, and obtain its coefficients using blind deconvolution. These estimated coefficients are then used to identify possible manipulations. We demonstrate the effectiveness of the proposed image authentication technique and compare our results with existing works.
12555245
Building Sparse Large Margin Classifiers
This paper presents an approach to build Sparse Large Margin Classifiers (SLMC) by adding one more constraint to the standard Support Vector Machine (SVM) training problem. The added constraint explicitly controls the sparseness of the classifier and an approach is provided to solve the formulated problem. When considering the dual of this problem. it can be seen that building an SLMC is equivalent to constructing an SVM with a modified kernel function. Further analysis of this kernel function indicates that the proposed approach essentially finds a discriminating subspace that can be spanned by a small number of vectors, and in this subspace different classes of data are linearly well separated. Experimental results over several classification benchmarks show that in most cases the proposed approach outperforms the state-of-art sparse learning algorithms.