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Human gait is an important biometric feature for person identification in surveillance videos because it can be collected at a distance without subject cooperation. Most existing gait recognition methods are based on Gait Energy Image (GEI). Although the spatial information in one gait sequence can be well represented by GEI, the temporal information is lost. To solve this problem, we propose a new...
In this paper, we focus on a study of the timing of different kinds of cars on the road. This information will enable us to infer the life style of the car owners. The results can further be used to guide marketing towards car owners and setting auto insurance policies. Conventionally, this kind of study is carried out by sending out questionnaires, which is limited in scale and diversity. To solve...
In the task of action recognition, object and scene can provide rich source of contextual information for analyzing human actions, as human actions often occur under particular scene settings with certain related objects. Therefore, we try to utilize the contextual object and scene for improving the performance of action recognition. Specifically, a latent structural SVM is introduced to build the...
Recognizing events in consumer videos is becoming increasingly important because of the enormous growth of consumer videos in recent years. Current researches mainly focus on learning from numerous labeled videos, which is time consuming and labor expensive due to labeling the consumer videos. To alleviate the labeling process, we utilize a large number of loosely labeled Web videos (e.g., from YouTube)...
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