0000000000143434
AUTHOR
Stan Sclaroff
Object Matching in Distributed Video Surveillance Systems by LDA-Based Appearance Descriptors
Establishing correspondences among object instances is still challenging in multi-camera surveillance systems, especially when the cameras’ fields of view are non-overlapping. Spatiotemporal constraints can help in solving the correspondence problem but still leave a wide margin of uncertainty. One way to reduce this uncertainty is to use ap- pearance information about the moving objects in the site. In this paper we present the preliminary results of a new method that can capture salient appearance characteristics at each camera node in the network. A Latent Dirichlet Allocation (LDA) model is created and maintained at each node in the camera network. Each object is encoded in terms of the…
Combining textual and visual cues for content-based image retrieval on the World Wide Web
A system is proposed that combines textual and visual statistics in a single index vector for content-based search of a WWW image database. Textual statistics are captured in vector form using latent semantic indexing (LSI) based on text in the containing HTML document. Visual statistics are captured in vector form using color and orientation histograms. By using an integrated approach, it becomes possible to take advantage of possible statistical couplings between the content of the document (latent semantic content) and the contents of images (visual statistics). The combined approach allows improved performance in conducting content-based search. Search performance experiments are report…
Online Multi-Person Tracking by Tracker Hierarchy
Tracking-by-detection is a widely used paradigm for multi-person tracking but is affected by variations in crowd density, obstacles in the scene, varying illumination, human pose variation, scale changes, etc. We propose an improved tracking-by-detection framework for multi-person tracking where the appearance model is formulated as a template ensemble updated online given detections provided by a pedestrian detector. We employ a hierarchy of trackers to select the most effective tracking strategy and an algorithm to adapt the conditions for trackers' initialization and termination. Our formulation is online and does not require calibration information. In experiments with four pedestrian t…
Gesture Modeling by Hanklet-Based Hidden Markov Model
In this paper we propose a novel approach for gesture modeling. We aim at decomposing a gesture into sub-trajectories that are the output of a sequence of atomic linear time invariant (LTI) systems, and we use a Hidden Markov Model to model the transitions from the LTI system to another. For this purpose, we represent the human body motion in a temporal window as a set of body joint trajectories that we assume are the output of an LTI system. We describe the set of trajectories in a temporal window by the corresponding Hankel matrix (Hanklet), which embeds the observability matrix of the LTI system that produced it. We train a set of HMMs (one for each gesture class) with a discriminative a…
Unifying Textual and Visual Cues for Content-Based Image Retrieval on the World Wide Web
A system is proposed that combines textual and visual statistics in a single index vector for content-based search of a WWW image database. Textual statistics are captured in vector form using latent semantic indexing based on text in the containing HTML document. Visual statistics are captured in vector form using color and orientation histograms. By using an integrated approach, it becomes possible to take advantage of possible statistical couplings between the content of the document (latent semantic content) and the contents of images (visual statistics). The combined approach allows improved performance in conducting content-based search. Search performance experiments are reported for…
Head Tracking via Robust Registration in Texture Map Images.
A novel method for 3D head tracking in the presence of large head rotations and facial expression changes is described. Tracking is formulated in terms of color image registration in the texture map of a 3D surface model. Model appearance is recursively updated via image mosaicking in the texture map as the head orientation varies. The resulting dynamic texture map provides a stabilized view of the face that can be used as input to many existing 2D techniques for face recognition, facial expressions analysis, lip reading, and eye tracking. Parameters are estimated via a robust minimization procedure; this provides robustness to occlusions, wrinkles, shadows and specular highlights. The syst…
Fully automatic, real-time detection of facial gestures from generic video
A technique for the detection of facial gestures from low resolution video sequences is presented. The technique builds upon the automatic 3D head tracker formulation of [M. La Cascia et al., 2000]. The tracker is based on the registration of a texture-mapped cylindrical model. Facial gesture analysis is performed in the texture map by assuming that the residual registration error can be modeled as a linear combination of facial motion templates. Two formulations are proposed and tested. In one formulation, the head and facial motion are estimated in a single, combined linear system. In the other formulation, head motion and then facial motion are estimated in a two-step process. The two-st…
Decoding Children's Social Behavior
We introduce a new problem domain for activity recognition: the analysis of children's social and communicative behaviors based on video and audio data. We specifically target interactions between children aged 1-2 years and an adult. Such interactions arise naturally in the diagnosis and treatment of developmental disorders such as autism. We introduce a new publicly-available dataset containing over 160 sessions of a 3-5 minute child-adult interaction. In each session, the adult examiner followed a semi-structured play interaction protocol which was designed to elicit a broad range of social behaviors. We identify the key technical challenges in analyzing these behaviors, and describe met…
Hankelet-based dynamical systems modeling for 3D action recognition
This paper proposes to model an action as the output of a sequence of atomic Linear Time Invariant (LTI) systems. The sequence of LTI systems generating the action is modeled as a Markov chain, where a Hidden Markov Model (HMM) is used to model the transition from one atomic LTI system to another. In turn, the LTI systems are represented in terms of their Hankel matrices. For classification purposes, the parameters of a set of HMMs (one for each action class) are learned via a discriminative approach. This work proposes a novel method to learn the atomic LTI systems from training data, and analyzes in detail the action representation in terms of a sequence of Hankel matrices. Extensive eval…
Joint Alignment and Modeling of Correlated Behavior Streams
The Variable Time-Shift Hidden Markov Model (VTS- HMM) is proposed for learning and modeling pairs of cor- related streams. Unlike previous coupled models for time series, the VTS-HMM accounts for varying time shifts be- tween correlated events in pairs of streams having different properties. The VTS-HMM is learned on a set of pairs of unaligned streams and, thus, learning entails simultaneous estimation of the varying time shifts and of the parameters of the model. The formulation is demonstrated in the analysis of videos of dyadic social interactions between children and adults in the Multimodal Dyadic Behavior Dataset (MMDB). In dyadic social interactions, an agent starts an interaction …
Path Modeling and Retrieval in Distributed Video Surveillance Databases
We propose a framework for querying a distributed database of video surveillance data in order to retrieve a set of likely paths of a person moving in the area under surveillance. In our framework, each camera of the surveillance system locally pro- cesses the data and stores video sequences in a storage unit and the metadata for each detected person in the distributed database. A pedestrian’s path is formulated as a dynamic Bayesian network (DBN) to model the dependencies between subsequent observa- tions of the person as he makes his way through the camera net- work. We propose a tool by which the analyst can pose queries about where a certain person appeared while moving in the site duri…
Fast, Reliable Head Tracking Under Varying Illumination
An improved technique for 3D head tracking under varying illumination conditions is proposed. The head is modeled as a texture mapped cylinder. Tracking is formulated as an image registration problem in the cylinder's texture map image. To solve the registration problem in the presence of lighting variation and head motion, the residual error of registration is modeled as a linear combination of texture warping templates and orthogonal illumination templates. Fast and stable on-line tracking is then achieved via regularized weighted least squares minimization of the registration error. The regularization term tends to limit potential ambiguities that arise in the warping and illumination te…
ImageRover: A Content-Based Image Browser for the World Wide Web
ImageRover is a search-by-image-content navigation tool for the World Wide Web (WWW). To gather images expediently, the image collection subsystem utilizes a distributed fleet of WWW robots running on different computers. The image robots gather information about the images they find, computing the appropriate image decompositions and indices, and store this extracted information in vector form for searches based on image content. At search time, users can iteratively guide the search through the selection of relevant examples. Search performance is made efficient through the use of an approximate, optimized k-d tree algorithm. The system employs a novel relevance feedback algorithm that se…