61362315
Cyclic articulated human motion tracking by sequential ancestral simulation
Accurate tracking of cyclic human motion in video data helps in developing computer-aided applications such as gait analysis, visual surveillance, patient rehabilitation, etc. This paper presents a novel technique for tracking cyclic human motion based on decomposing complex cyclic motion into components and maintaining coupling between components. The decomposition reduces the dimensionality of the problem and enables a graphical modeling of the articulated human body. The coupling between components is modeled by their phase relationship and represented as directed edges in Bayesian networks and undirected edges in Markov random fields. Such coupling is maintained in tracking through ancestral simulation (AS) and Markov potentials in a sequential Monte Carlo tracking framework. We show that the approach handles severe self-occlusion and foreign body occlusion with improved accuracy and efficiency.
782406
Data Compression
44378446
Component-Oriented Digital Signal Processors
9272685
Genetic algorithm for affine point pattern matching
Point pattern matching (PPM) is an important topic in the fields of computer vision and pattern recognition. According to if there exists a one to one mapping between the two point sets to be matched, PPM can be divided into the case of complete matching and the case of incomplete matching. According to if utilizing information other than 2-D image coordinates, PPM can be divided into labelled point-matching case and unlabelled point-matching case. Using partial Hausdorff distance, this paper presents a genetic algorithm (GA) based method to solve the incomplete unlabelled matching problem under general affine transformation. Since it successfully reduces the solution space of GA by constructing 'feature ellipses' of point sets, the method can achieve high computing efficiency and good matching results. Theoretical analysis and simulation results show that the new algorithm is very effective.
10631202
Real-time scheduling in a programmable radar signal processor
The new trend of designing radar digital signal processors is not only to improve their processing speed by adopting the parallel multi-processor architecture but also to make their infrastructure flexible so that one generic digital signal processor framework can be applied to a variety of different radar systems. The key technology to make such radar digital signal processor architecture programmable, or flexible, is the scheduler which manages resources of digital signal processing in real-time according to system requirements. In this paper, the architecture of the programmable radar signal processor (PRSP) is presented, and a real-time scheduling algorithm used in PRSP is thoroughly discussed.
12856888
On the rate distortion function of Bernoulli Gaussian sequences
We study the rate distortion function of the Bernoulli-Gaussian random variable which can be used to model sparse signals. Both lower and upper bounds on the rate distortion function are given.We show that the bounds are almost tight in the low distortion regime for sparse signals. Interestingly, a naive coding scheme is near-optimal in this scenario.
1776041
The design of distributed real-time video analytic system
Video has become an indispensable carrier of information and requires extremely computation expensive analysis to understand high level semantics. The computational difficulties in extracting embedded information and bridging the semantic gap present the major challenges in interoperability, scalability and real-time response of video analytic systems. In this paper, we propose a distributed scalable infrastructure VAP (Video Analytic Platform) for supporting real-time video stream analysis. In VAP, the application requirements are represented as a Directed Acrylic Graph (DAG), where nodes stand for video analysis computation modules and links show data flow and dependencies between nodes. VAP leverages UIMA (Unstructured Information Management Architecture) framework as the data flow control engine and multiple commodity databases as the storage and computation resources. The actual executions of video analysis computation modules have been pushed down into database engines to minimize the data movement cost. We initially choose video surveillance in retail store as a representative application domain. As a case study, a prototype system has been developed to achieve fundamental functions of real-time video surveillance, including video capture/store, human detection/tracking and customer shopping trajectory analysis.