586486
Object-Based Access to TV Rushes Video
Recent years have seen the development of different modalities for video retrieval. The most common of these are (1) to use text from speech recognition or closed captions, (2) to match keyframes using image retrieval techniques like colour and texture [6] and (3) to use semantic features like “indoor”, “outdoor” or “persons”. Of these, text-based retrieval is the most mature and useful, while image-based retrieval using low-level image features usually depends on matching keyframes rather than whole-shots. Automatic detection of video concepts is receiving much attention and as progress is made in this area we will see consequent impact on the quality of video retrieval. In practice it is the combination of these techniques which realises the most useful, and effective, video retrieval as shown by us repeatedly in TRECVid [5].
7244802
Design, implementation and testing of an interactive video retrieval system
In this paper we present and discuss the system we developed for the search task of the TRECVID 2002, and its evaluation in an interactive search task. To do this we will look at the strategy we used in designing the system, and we discuss and evaluate the experiments used to determine the value and effectiveness of one system incorporating both feature evidence and transcript retrieval compared to a transcript-only retrieval system. Both systems tested are built on the foundation of the Físchlár System developed and running for a number of years at the CDVP. The system is fully MPEG-7 compliant and uses XML for exchange of information within the overall architecture.
15223970
User Interface Issues for Browsing Digital Video
In this paper we examine a suite of systems for content-based indexing and browsing of digital video and we identify a superset of features and functions which are provided by these systems. From our classification of these we have identified that common to all is the fact of being predominantly technology-based, with little attention paid to actual user requirements. As part of our work we are developing an application for content-based browsing of digital video which will incorporate the most desirable but achievable of the functions of other systems. This will be achieved via a series of continuously refined demonstrator systems from Spring 1999 onwards which will be subjected to analysis of performance in terms of user.
15518000
MediAssist: Using Content-Based Analysis and Context to Manage Personal Photo Collections
We present work which organises personal digital photo collections based on contextual information, such as time and location, combined with content-based analysis such as face detection and other feature detectors. The MediAssist demonstration system illustrates the results of our research into digital photo management, showing how a combination of automatically extracted context and content-based information, together with user annotation, facilitates efficient searching of personal photo collections.
2326376
Dublin City University Video Track Experiments for TREC 2002
Dublin City University participated in the Feature Extraction task and the Search task of the TREC-2002 Video Track. In the Feature Extraction task, we submitted 3 features: Face, Speech, and Music. In the Search task, we developed an interactive video retrieval system, which incorporated the 40 hours of the video search test collection and supported user searching using our own feature extraction data along with the donated feature data and ASR transcript from other Video Track groups. This video retrieval system allows a user to specify a query based on the 10 features and ASR transcript, and the query result is a ranked list of videos that can be further browsed at the shot level. To evaluate the usefulness of the feature-based query, we have developed a second system interface that provides only ASR transcript-based querying, and we conducted an experiment with 12 test users to compare these 2 systems. Results were submitted to NIST and we are currently conducting further analysis of user performance with these 2 systems.
14600812
Implementation and Analysis of Several Keyframe-Based Browsing Interfaces to Digital Video
In this paper we present a variety of browsing interfaces for digital video information. The six interfaces are implemented on top of Fischlar, an operational recording, indexing, browsing and playback system for broadcast TV programmes. In developing the six browsing interfaces, we have been informed by the various dimensions which can be used to distinguish one interface from another. For this we include layeredness (the number of "layers" of abstraction which can be used in browsing a programme), the provision or omission of temporal information (varying from full timestamp information to nothing at all on time) and visualisation of spatial vs. temporal aspects of the video. After introducing and defining these dimensions we then locate some common browsing interfaces from the literature in this 3-dimensional "space" and then we locate our own six interfaces in this same space. We then present an outline of the interfaces and include some user feedback.
8746722
Parameter space exploration with Gaussian process trees
Computer experiments often require dense sweeps over input parameters to obtain a qualitative understanding of their response. Such sweeps can be prohibitively expensive, and are unnecessary in regions where the response is easy predicted; well-chosen designs could allow a mapping of the response with far fewer simulation runs. Thus, there is a need for computationally inexpensive surrogate models and an accompanying method for selecting small designs. We explore a general methodology for addressing this need that uses non-stationary Gaussian processes. Binary trees partition the input space to facilitate non-stationarity and a Bayesian interpretation provides an explicit measure of predictive uncertainty that can be used to guide sampling. Our methods are illustrated on several examples, including a motivating example involving computational fluid dynamics simulation of a NASA reentry vehicle.
16122349
Feature-Based Image Watermarking Method Using Scale-Invariant Keypoints
This paper addresses feature-based image watermarking methods for digital contents. Most previous watermarking algorithms suffer from geometric distortion attacks that desynchronize the location of the inserted watermark. In order to synchronize the watermark location, watermark synchronization should be performed. One solution for watermark synchronization is to use image features. This paper describes a feature-based watermarking method based on scale-invariant keypoints. We extract feature points from the scale-invariant keypoint extractor and then decompose feature points into a set of disjoint triangles. These triangles are watermarked by an additive spread-spectrum method on the spatial domain. We perform an intensive simulation in comparison with other feature-based watermarking methods using 100 test images. Results show that the proposed method is considerably robust against both geometric distortion attacks and signal processing attacks listed in Stirmark 3.1.
17638877
Feature-Based Synchronization of Video and Background Music
We synchronize background music with a video by changing the timing of music, an approach that minimizes the damage to music data. Starting from a MIDI file and video data, feature points are extracted from both sources, paired, and then synchronized using dynamic programming to time-scale the music. We also introduce the music graph, a directed graph that encapsulates connections between many short music sequences. By traversing a music graph, we can generate large amounts of new background music, in which we expect to find a sequence which matches the video features better than the original music.
35319384
Gesture spotting from continuous hand motion
This paper proposes a new method of gesture spotting based on the Hidden Markov Model (HMM) that extracts meaningful gestures from continuous hand motion. To remove non-gesture patterns from input patterns, we introduce the threshold model that calculates the threshold likelihood of the input pattern and helps to qualify an input pattern as a gesture. The proposed method extracts gestures with 93.38% reliability.
14075351
A Dynamic Bayesian Network Model for Autonomous 3D Reconstruction from a Single Indoor Image
When we look at a picture, our prior knowledge about the world allows us to resolve some of the ambiguities that are inherent to monocular vision, and thereby infer 3d information about the scene. We also recognize different objects, decide on their orientations, and identify how they are connected to their environment. Focusing on the problem of autonomous 3d reconstruction of indoor scenes, in this paper we present a dynamic Bayesian network model capable of resolving some of these ambiguities and recovering 3d information for many images. Our model assumes a "floorwall" geometry on the scene and is trained to recognize the floor-wall boundary in each column of the image. When the image is produced under perspective geometry, we show that this model can be used for 3d reconstruction from a single image. To our knowledge, this was the first monocular approach to automatically recover 3d reconstructions from single indoor images.