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Common benchmark data sets, standardized performance metrics, and baseline algorithms have demonstrated considerable impact on research and development in a variety of application domains. These resources provide both consumers and developers of technology with a common framework to objectively compare the performance of different algorithms and algorithmic(More)
— This paper presents a novel method for automatic spotting (temporal segmentation) of facial expressions in long videos comprising of continuous and changing expressions. The method utilizes the strain impacted on the facial skin due to the non-rigid motion caused during expressions. The strain magnitude is calculated using the central difference method(More)
—In this paper, we propose a method to model the material constants (Young's modulus) of the skin in sub-regions of the face from the motion observed in multiple facial expressions and present its relevance to an image analysis task such as face verification. On a public database consisting of 40 subjects undergoing some set of facial motions associated(More)
The need for empirical evaluation metrics and algorithms is well acknowledged in the field of computer vision. The process leads to precise insights to understanding current technological capabilities and also helps in measuring progress. Hence designing good and meaningful performance measures is very critical. In this paper, we propose two comprehensive(More)
The success of forensic identification largely depends on the availability of strong evidence or traces that substantiate the prosecution hypothesis that a certain person is guilty of crime. In light of this, extracting subtle evidences which the criminals leave behind at the crime scene will be of valuable help to investigators. We propose a novel method(More)
Text detection and tracking is an important step in a video content analysis system as it brings important semantic clues which is a vital supplemental source of index information. While there has been a significant amount of research done on video text detection and tracking , there are very few works on performance evaluation of such systems. Evaluations(More)
We present a finite element modeling based approach to compute strain patterns caused by facial deformation during expressions in videos. A sparse motion field computed through a robust optical flow method drives the FE model. While the geometry of the model is generic, the material constants associated with an individual's facial skin are learned at a(More)
—Handwritten text line segmentation on real-world data presents significant challenges that cannot be overcome by any single technique. Given the diversity of approaches and the recent advances in ensemble-based combination for pattern recognition problems, it is possible to improve the segmentation performance by combining the outputs from different line(More)
— This paper presents a method for face identification under adverse conditions by combining regular, frontal face images with facial strain maps using score-level fusion. Strain maps are generated by calculating the central difference method of the optical flow field obtained from each subject's face during the open mouth expression. Subjects were recorded(More)
Combining features from multiple, heterogeneous, audio visual sources can significantly improve retrieval performance in consumer domain videos. However, such videos often contain unrelated overlaid audio content, or have significant camera motion to reliably extract visual features. We present an approach, which overcomes errors in individual feature(More)