A ROBUST GA/KNN BASED HYPOTHESIS VERIFICATION SYSTEM FOR VEHICLE DETECTION

ABSTRACT Vehicle detection is an important issue in driver assistance systems and self-guided vehicles that include

Analysis and recognition of human actions with flow features and temporal models

This work focuses the recognition of complex human activities in video data. A combination of new features and techniques from speech recognition is used to realize a recognition of action units and their combinations in video sequences. The presented approach shows how motion information gained from video data can be used to interpret the underlying structural information of actions and how higher level models allow an abstraction of different motion categories beyond simple classification

A descriptor combining MHI and PCOG for human motion classification

The performance of human motion classification and recognition systems is highly dependent on the distinctiveness and robustness of the feature descriptor. In this paper, a new descriptor containing motion, shape and spatial layout information is proposed, therefore it is more effective for action modeling and is suitable for detecting and recognizing a variety of actions. Experiments show that the proposed descriptor outperforms other existing methods, such as Moment Invariants and Histogram of Oriented Gradients, on recognizing human motions in an indoor environment with a stationary camera