A Modern Computer Vision Library

View the Project on GitHub liuliu/ccv


This is open source implementation of object detection algorithm: brightness binary feature it is an extension/modification of original haar-like feature with adaboost, featured faster computation and higher accuracy (current highest accuracy close-source face detector is based on the same algorithm)


void ccv_bbf_classifier_cascade_new(ccv_dense_matrix_t **posimg, int posnum, char **bgfiles, int bgnum, int negnum, ccv_size_t size, const char *dir, ccv_bbf_new_param_t params)

Create a new BBF classifier cascade from given positive examples and background images. This function has a hard dependency on GSL.



ccv_bbf_detect_objects(ccv_dense_matrix_t *a, ccv_bbf_classifier_cascade_t **cascade, int count, ccv_bbf_param_t params)

Using a BBF classifier cascade to detect objects in a given image. If you have several classifier cascades, it is better to use them in one method call. In this way, ccv will try to optimize the overall performance.

return: A ccv_array_t of ccv_comp_t for detection results.



ccv_bbf_read_classifier_cascade(const char *directory)

Read BBF classifier cascade from working directory.

return: A classifier cascade, 0 if no valid classifier cascade available.


void ccv_bbf_classifier_cascade_free(ccv_bbf_classifier_cascade_t *cascade)

Free up the memory of BBF classifier cascade.


ccv_bbf_classifier_cascade_read_binary(char *s)

Load BBF classifier cascade from a memory region.

return: A classifier cascade, 0 if no valid classifier cascade available.


int ccv_bbf_classifier_cascade_write_binary(ccv_bbf_classifier_cascade_t *cascade, char *s, int slen)

Write BBF classifier cascade to a memory region.

return: The actual size of the binarized BBF classifier cascade, if this size is larger than slen, please reallocate the memory region and do it again.

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