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Convolutional neural network (CNN) has drawn increasing interest in visual tracking, among which fully-convolutional Siamese network based method (SiamFC) is quite popular due to its competitive performance in both precision and efficiency. Generally, SiamFC captures robust semantics from high-level features in the last layer but ignores detailed spatial features in earlier layers, thus tending to...
Due to the superiority in handling label ambiguity, multiple instance learning (MIL) has been introduced into adaptive tracking-by-detection methods to alleviate drift and yields promising tracking performance. However, the MIL tracker assumes that all samples in a positive bag contribute equally to the bag probability, which ignores sample importance. To address this issue, in this paper we propose...
Aiming at the problem how to express relevant relationship between multiple targets, we propose an approach based on the tracking-by-detection (TBD) strategy, where detections from the HOG classifier are regarded as image evidence. Focusing on the issue of localization uncertainty, data association based on greedy heuristics is executed iteratively to retrieve from the erroneous candidate locations...
The decomposed information of power consumption of household appliances is meaningful for scheduling the appliances and the reduction in home energy use. This paper presents a novel nonintrusive load identification method based on continuous quadratic 0–1 programming. Extensive lab tests have demonstrated that the proposed technique can provide adequate load identification accuracy for residential...
Speech with various emotions aggravates the performance of speaker recognition system. The existing speaker modeling disregards the match of the emotional state between training and testing speech, and the systems suffer the lapsus of the emotion recognition as to practical application. We propose an alternative approach that exploits the prosodic difference to cluster affective speech, and then builds...
In this paper, a large emotional speech database MASC (Mandarin affective speech corpus) is introduced. The database contains recordings of 68 native speakers (23 female and 45 male) and five kinds of emotional states: neutral, anger, elation, panic and sadness. Each speaker pronounces 5 phrases, 10 sentences for three times for each emotional states and 2 paragraphs only for neutral. These materials...
One of the largest challenges in speaker recognition applications is dealing with speaker-emotion variability. In this paper, we further investigate the rules based feature modification for robust speaker recognition with emotional speech. Specifically, we learn the rules of prosodic features modification from a small amount of the content matched source-target pairs. Features with emotion information...
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