The role of temporal synchrony in the facilitation of perceptual learning during prenatal development

This study explored the critical features of temporal synchrony for the facilitation of prenatal perceptual learning with respect to unimodal stimulation using an animal model, the bobwhite quail. The following related hypotheses were examined: (1) the availability of temporal synchrony is a critical feature to facilitate prenatal perceptual learning, (2) a single temporally synchronous note is sufficient to facilitate prenatal perceptual learning, with respect to unimodal stimulation, and (3) in situations where embryos are exposed to a single temporally synchronous note, facilitated perceptual learning, with respect to unimodal stimulation, will be optimal when the temporally synchronous note occurs at the onset of the stimulation bout. To assess these hypotheses, two experiments were conducted in which quail embryos were exposed to various audio-visual configurations of a bobwhite maternal call and tested at 24 hr after hatching for evidence of facilitated prenatal perceptual learning with respect to unimodal stimulation. Experiment 1 explored if intermodal equivalence was sufficient to facilitate prenatal perceptual learning with respect to unimodal stimulation. A Bimodal Sequential Temporal Equivalence (BSTE) condition was created that provided embryos with sequential auditory and visual stimulation in which the same amodal properties (rate, duration, rhythm) were made available across modalities. Experiment 2 assessed: (a) whether a limited number of temporally synchronous notes are sufficient for facilitated prenatal perceptual learning with respect to unimodal stimulation, and (b) whether there is a relationship between timing of occurrence of a temporally synchronous note and the facilitation of prenatal perceptual learning. Results revealed that prenatal exposure to BSTE was not sufficient to facilitate perceptual learning. In contrast, a maternal call that contained a single temporally synchronous note was sufficient to facilitate embryos’ prenatal perceptual learning with respect to unimodal stimulation. Furthermore, the most salient prenatal condition was that which contained the synchronous note at the onset of the call burst. Embryos’ prenatal perceptual learning of the call was four times faster in this condition than when exposed to a unimodal call. Taken together, bobwhite quail embryos’ remarkable sensitivity to temporal synchrony suggests that this amodal property plays a key role in attention and learning during prenatal development.

An incremental multilinear system for human face learning and recognition

This dissertation establishes a novel system for human face learning and recognition based on incremental multilinear Principal Component Analysis (PCA). Most of the existing face recognition systems need training data during the learning process. The system as proposed in this dissertation utilizes an unsupervised or weakly supervised learning approach, in which the learning phase requires a minimal amount of training data. It also overcomes the inability of traditional systems to adapt to the testing phase as the decision process for the newly acquired images continues to rely on that same old training data set. Consequently when a new training set is to be used, the traditional approach will require that the entire eigensystem will have to be generated again. However, as a means to speed up this computational process, the proposed method uses the eigensystem generated from the old training set together with the new images to generate more effectively the new eigensystem in a so-called incremental learning process. In the empirical evaluation phase, there are two key factors that are essential in evaluating the performance of the proposed method: (1) recognition accuracy and (2) computational complexity. In order to establish the most suitable algorithm for this research, a comparative analysis of the best performing methods has been carried out first. The results of the comparative analysis advocated for the initial utilization of the multilinear PCA in our research. As for the consideration of the issue of computational complexity for the subspace update procedure, a novel incremental algorithm, which combines the traditional sequential Karhunen-Loeve (SKL) algorithm with the newly developed incremental modified fast PCA algorithm, was established. In order to utilize the multilinear PCA in the incremental process, a new unfolding method was developed to affix the newly added data at the end of the previous data. The results of the incremental process based on these two methods were obtained to bear out these new theoretical improvements. Some object tracking results using video images are also provided as another challenging task to prove the soundness of this incremental multilinear learning method.

The Role of Temporal Synchrony in the Facilitation of Perceptual Learning during Prenatal Development

This study explored the critical features of temporal synchrony for the facilitation of prenatal perceptual learning with respect to unimodal stimulation using an animal model, the bobwhite quail. The following related hypotheses were examined: (1) the availability of temporal synchrony is a critical feature to facilitate prenatal perceptual learning, (2) a single temporally synchronous note is sufficient to facilitate prenatal perceptual learning, with respect to unimodal stimulation, and (3) in situations where embryos are exposed to a single temporally synchronous note, facilitated perceptual learning, with respect to unimodal stimulation, will be optimal when the temporally synchronous note occurs at the onset of the stimulation bout. To assess these hypotheses, two experiments were conducted in which quail embryos were exposed to various audio-visual configurations of a bobwhite maternal call and tested at 24 hr after hatching for evidence of facilitated prenatal perceptual learning with respect to unimodal stimulation. Experiment 1 explored if intermodal equivalence was sufficient to facilitate prenatal perceptual learning with respect to unimodal stimulation. A Bimodal Sequential Temporal Equivalence (BSTE) condition was created that provided embryos with sequential auditory and visual stimulation in which the same amodal properties (rate, duration, rhythm) were made available across modalities. Experiment 2 assessed: (a) whether a limited number of temporally synchronous notes are sufficient for facilitated prenatal perceptual learning with respect to unimodal stimulation, and (b) whether there is a relationship between timing of occurrence of a temporally synchronous note and the facilitation of prenatal perceptual learning. Results revealed that prenatal exposure to BSTE was not sufficient to facilitate perceptual learning. In contrast, a maternal call that contained a single temporally synchronous note was sufficient to facilitate embryos’ prenatal perceptual learning with respect to unimodal stimulation. Furthermore, the most salient prenatal condition was that which contained the synchronous note at the onset of the call burst. Embryos’ prenatal perceptual learning of the call was four times faster in this condition than when exposed to a unimodal call. Taken together, bobwhite quail embryos’ remarkable sensitivity to temporal synchrony suggests that this amodal property plays a key role in attention and learning during prenatal development.

Exploring Hidden Coherent Feature Groups and Temporal Semantics for Multimedia Big Data Analysis

Thanks to the advanced technologies and social networks that allow the data to be widely shared among the Internet, there is an explosion of pervasive multimedia data, generating high demands of multimedia services and applications in various areas for people to easily access and manage multimedia data. Towards such demands, multimedia big data analysis has become an emerging hot topic in both industry and academia, which ranges from basic infrastructure, management, search, and mining to security, privacy, and applications. Within the scope of this dissertation, a multimedia big data analysis framework is proposed for semantic information management and retrieval with a focus on rare event detection in videos. The proposed framework is able to explore hidden semantic feature groups in multimedia data and incorporate temporal semantics, especially for video event detection. First, a hierarchical semantic data representation is presented to alleviate the semantic gap issue, and the Hidden Coherent Feature Group (HCFG) analysis method is proposed to capture the correlation between features and separate the original feature set into semantic groups, seamlessly integrating multimedia data in multiple modalities. Next, an Importance Factor based Temporal Multiple Correspondence Analysis (i.e., IF-TMCA) approach is presented for effective event detection. Specifically, the HCFG algorithm is integrated with the Hierarchical Information Gain Analysis (HIGA) method to generate the Importance Factor (IF) for producing the initial detection results. Then, the TMCA algorithm is proposed to efficiently incorporate temporal semantics for re-ranking and improving the final performance. At last, a sampling-based ensemble learning mechanism is applied to further accommodate the imbalanced datasets. In addition to the multimedia semantic representation and class imbalance problems, lack of organization is another critical issue for multimedia big data analysis. In this framework, an affinity propagation-based summarization method is also proposed to transform the unorganized data into a better structure with clean and well-organized information. The whole framework has been thoroughly evaluated across multiple domains, such as soccer goal event detection and disaster information management.